text:
|Publication number
|Publication type
|Application number
|Publication date
|Jun 14, 1988
|Filing date
|Nov 6, 1985
|Priority date
|Nov 6, 1985
|Fee status
|Publication number
|Ira A. Gerson, Brett L. Lindsley
|Original Assignee
|Motorola Inc.
|Export Citation
|BiBTeX, EndNote, RefMan
|Patent Citations (12), Non-Patent Citations (20), Referenced by (54), Classifications (7), Legal Events (6)
|External Links: USPTO, USPTO Assignment, Espacenet
The present invention relates to the practice of generating reliable word templates from speech utterances for a speech recognition system and, more particularly, to the practice of generating reliable word templates by averaging repetitious speech during word training for a user dependent speech recognition system.
A typical method of word template generation is to use a single utterance of a given word as the word template. This has been known to cause problems due to the fluctuation in which words are spoken by the user of the system. Words can be distorted by the speed in which they are spoken as well as by physical irregularities in the speaker's voice. For example, a word will distort when the user has a cold or when the user's lips smack.
Another typical method of word template generation is to use multiple training utterances stored as individual templates for a given word. Although this method can realize good accuracy in matching spoken words to the prestored word templates, it may be impractical due to the excessive computation time and extensive memory it requires.
Because of problems related to these methods, there has been a number of word template generation schemes developed which use the concept of averaging spoken words during voice training. Words spoken for training are referred to as tokens. Although the word "token" implies a single spoken word, a "token" can merely represent a short phrase. The goal in averaging tokens in a word template generation scheme is to generate a word template which best typifies the word as spoken by the speech recognition system user. Prior art methods which average training tokens generate the word template from tokens which disproportionately contribute to the resultant word template.
In a paper by Y. J. Liu, entitled "On Creating Averaging Methods", ICASSP 1984 pp. 9.1.1 through 9.1.4, described are a few techniques for generating templates by averaging. The first technique is called `Dynamic Averaging`. The first requirement in this technique is to choose a token `whose length is representative`. Subsequent tokens are averaged into this chosen token, each mapped to the `representative length`. The disadvantage of this technique is twofold. The first disadvantage is that if one of the tokens is not of a similar length, mapping its length onto a time axis of a chosen does not allow the token to contribute to the averaged token with respect to length. If the token is at all representative of the spoken word, it should be averaged in data and length. If the token is not representative of the spoken word, it should not be averaged at all.
The second disadvantage of this technique is that the resultant word template is dependent on the order in which the tokens are averaged into the chosen token. Hence, the optimal resultant word template cannot be found since the optimal order in averaging the tokens cannot be determined.
The second method Liu describes is called `Dynamic Local Averaging`. This method also requires that a token be chosen which is of "representative length". This chosen word is then averaged with other spoken words according to the distances between frames within the words. Frames from words with minimum corresponding frame distances are averaged together to generate the representative word template. Accordingly, this method chooses a token, and then averages it with other tokens along a path in time, but not necessarily along a global time alignment path to produce the optimal alignment.
The last method Liu describes, `Linear Averaging`, requires choosing a `common length` and linearly changing the time axis of each token to that common length. The tokens are then averaged vertically, according to aligned frames. This technique may not generate a very representative word template.
Notwithstanding the peculiarities of these prior art word template generation methods, each method requires an initial storage of all original tokens. Since most speech recognition systems are memory limited, it is usually desirable that any spare memory be used for vocabulary storage. This additional memory requirement of the above discussed methods only further burdens the speech recognition system.
When a user is training the speech recognition system, the tokens are meant to each be representative of the word as spoken by the user. Each token should have an equal contribution to the generated word template, unless of course, one token happens to be entirely different from the others. In summary, the desired results for a word template generation method is one which produces a final word template with the following results:
The final word template should have an averaged time axis such that each token equally contributes to the final word template;
When the average length of all the tokens is fractional, the generated word template will have a length which is rounded off to the closest number of frames;
As the number of tokens used in the averaging process increases, each additional token should have a reduced effect on the word template being generated as a whole;
The memory required for generating the word template should be a minimum; and
The generated word template is independent of the order in which the tokens are averaged.
In practicing the present invention, provided is a method and system for generating a final word template in a speech recognition system where speech is represented by data in frames of equal time intervals. The invention includes forming an interim template representative of at least one token, generating a time alignment path between the interim template and an additional token, mapping frames from the interim template and the token along the time alignment path onto an an averaged axis, and combining data associated with the mapped frames to produce composite frames representative of the final word template.
An additional aspect of the invention includes weighting the data representing the interim template proportional to the number of tokens the interim template represents.
FIG. 1 is a flowchart of a speech recognition word training procedure, according to the present invention.
FIG. 2a, 2b and 2c are sequence of vector diagrams displaying directional weighting for a time alignment path, according to the present invention.
FIG. 3 is a graph showing an example of a token being combined with a master template, according to the present invention.
FIG. 4 is a flowchart showing, specifically, how a token is combined with a master template for averaging, according to the present invention.
FIG. 5 is a graph, similar to the graph in FIG. 3, showing a more complex example for combining a token with a master template, according to the present invention.
FIG. 6 is a block diagram of a speech recognition system in accordance with the present invention.
The flowchart of FIG. 1 depicts a general description of a training procedure which averages tokens to generate an accurate representative word template. The procedure begins by obtaining a token and designating it as the master template, block 10. The term "master template" refers to a template which may be combined with additional tokens. Accordingly, the term "interim template" is used interchangeably with "master template". The master template's data is assigned a weight equal to one, block 12, since it represents only one token. Another token is obtained, block 14, which is referred to as the new token. Only a master template and a new token are required to be stored throughout this entire procedure. For a large number of tokens, this substantially reduces the required memory allocation.
The new token is dynamically time warped with the master template and the distance between them is determined, block 16. The distance is a measure of acoustic similarity commonly generated by comparing the representative data from each.
A dynamic time warp function maps two words, which may have different lengths, of similar acoustic information, onto a distance grid. Dynamic time warping is commonly used in most speech recognition applications using word templates. Nevertheless, a discussion of the preferred warping technique follows.
The preferred dynamic time warping algorithm uses a symmetric form of local path constraints as proposed by Sakoe and Chiba in a paper entitled "Dynamic Programming Algorithm Optimization for Spoken Word Recognition", ASSP Vol. 26, No. 1 February 1978. Sakoe and Chiba describe and define the fundamentals of time-normalized distance between two words, or tokens as the case may be. An adjustment window is implemented to define local slope constraints limiting the time deviation measured between the two words. The preferred symmetric form chosen for this application has local constraints which force a diagonal move after any horizontal or vertical move on the distance grid. This is defined by the dynamic programming equation through the recurrence relation, g(i,j). The constraints are: ##EQU1## where d(i,j) is a distance function between frame i of word 1 frame j of word 2. The recursion is initialized at g(1,1)=2 d(1,1) and the time normalized distance is found by g(I,J)/(I+J), where I and J are the lengths of words 1 and 2 respectively.
Using these local constraints, the maximum ratio of which the longest word can be warped to the shortest word is two. Due to this limited warping constraint, the global limit window used is that proposed by Paliwal, Agarwal and Sinha in a paper entitled "A Modification Over Sakoe and Chiba's Dynamic Time Warping Algorithm for Isolated Word Recognition", ICASSP, 1982, pp. 1259-1261. This allows freedom to the global limit window constraints such that the window's center is a line joining the points (1,1) and (I,J), allowing the path formed between the two words to remain within local boundaries. For each point within the global window, a pointer is used to indicate the direction to the previous point on the minimal distance path. Linking these points defines an optimal time alignment path for the two words.
From block 16, flow moves to block 18 where, a check is made to determine if the total distance between these two words is reasonable, i.e. a threshold test. If the distance between the master template and the new token is greater than a predetermined amount, then the token will not be averaged into the master template. This prevents a bad token from being considered in the averaging process along with the other tokens.
If the threshold is reached, flow moves to block 20 and a test is performed to determine if the master template represents only one token. If so, the new token replaces the master template, block 22, and the process repeats at block 14. If the master template represents more than one token, a test is performed to determine if the master template has been replaced more than three times since the last averaging, block 24. If this test results in the affirmative, flow continues at block 22 for another replacement of the master template. If the result is not in the affirmative, flow moves to block 14 for a repeat of the process using another new token. The number "three" in block 24 is chosen to prevent tokens from being averaged which are not similar to other tokens. If the distance threshold test, block 18, indicates that three or more tokens are not similar to the master template, it is very likely that the master template is not representative of the spoken word.
If the distance threshold test, block 18, indicates a similarity between the new token and the master template, flow moves to block 26 where the new token is averaged with the master template. The result in averaging the master template with the new token is a new master template. Details of this block are subsequently discussed with FIG. 4.
The weight assigned to the master template is incremented at block 28, since the master template now represents another token.
A test is performed at block 30 to determine if the desired number of tokens have been averaged. If not, another token is obtained, block 14, and the process repeats until the desired number of tokens is represented by the master template.
Referring now to FIG. 2(a), shown is a vector diagram where a new token, with frames designated by `i`, is plotted against a master template, with frames designated by `j`, on a distance grid. Dynamic time warping is used to optimally align frames `i` to frames `j`. The horizontal vector, labeled 1, defines a weight of magnitude 1 when the path which aligns the two words travels horizontally. The vertical vector, labeled mw, indicates the master weight and carries a weight of "mw" whenever the path travels vertically. Likewise, the diagonal vector, mw+1, carries a weight of ("mw"+1) whenever the path travels diagonally. These weight assignments are used in the averaging procedure, block 18 of FIG. 1, for combining the new token to the master template.
FIG. 2(b) shows an example of weighting in which mw=1, the horizontal weight is 1 and the diagonal weight is 2. This weighting example indicates that the master template is comprised of only one token, i.e. there has not yet been an averaging to combine two tokens. After the first two tokens are combined the master weight is 2 due to the newly formed master template. After a third token is combined with the first two, the master weight becomes 3.
FIG. 2(c) shows a vector diagram in which mw=3. The diagonal move is (mw+1), or 4. As an increasing number of tokens are averaged into the master template, each new token has less effect on the master template. In fact, as the number of tokens combined in the master template increases, the token being averaged has less effect on the length of the master template and also on the features, or representative data, which make-up the master template.
FIG. 3 shows a graph in which two words are time aligned according to the dynamic time warping algorithm previously discussed. The frames of the new token are plotted along the horizontal time axis, and the frames of the master template are plotted along the vertical time axis. The line in the graph represents the path of minimal distance between these two words, calculated by the recurrence relation, g(i,j). Each circle along the line defines at least one frame from the new token which will be averaged with at least one frame from the master template. This example represents the case in which no tokens have previously been combined, i.e. mw=1.
The averaging procedure includes a variable known as the sum of weights, SOW. SOW is the sum of the lengths of all the tokens combined. SOW is used to accumulate the number of weighted frames as an account for when a frame is to be output. Each time a move is made to another point on the path, the weight for the direction taken is added to SOW. Since the total weight for the master template plus the new token is independent of the time alignment path, SOW from the endpoint (I,J) to the starting point (1,1) is:
SOW=(I-1)+mw*(J-1) (equation 1)
where I is the length of the new token in frames and J is the length of the master template in frames, with time axis i and j, respectively.
SOW is initialized at point (I,J) with a weight of (mw+1)/2 and updated by (mw+1)/2 at point (1,1). Using these value delimiters, the total SOW, after backtracking from end to beginning, is:
SOWtotal =I+(mw * J). (equation 2)
This is the true sum of lengths of all averaged tokens. This can be illustrated by considering two words being combined, each with a frame length of 2. Without using the value delimiters, equation 1 results in SOW=2 since mw equals 1. This is not representative of the definition of SOW, i.e. the sum of the lengths of all the tokens combined. However, using the value delimiters, equation 2 results in SOWtotal =4, the total length of this combination.
A frame is output if SOW becomes greater than or equal to the master weight. After each frame is output, SOW is normalized by subtracting the number of tokens, (mw+1). This normalization procedure produces the number of frames in the final word template which is equal to the average length of all tokens combined, or equivalently, the weighted average length of the master template and the new token.
Accordingly, the procedure begins by initializing SOW to 1 and averaging from point (7,5) of the graph of FIG. 3. The formation of an averaged frame, depicted by the circles, is defined by adding to SOW, the weight of the first move along the path. The first move is diagonal with an assigned weight of 2. SOW becomes 3. According to the present invention, a properly formed frame does not accumulate a SOW greater than or equal to (mw+1). If (mw+1) is reached by SOW, (mw+1) is subtracted from SOW and a frame is output. In this example, since SOW is greater than (mw+1), a frame at point (7,5) is output, and SOW is normalized to 1. This output frame is comprised of an average of representing data from frame 7, of the new token, and representing data from frame 5 of the master template. If mw was equal to 2 in this example, the output frame would be formed by averaging two parts of frame 5 to one part of frame 7, since each token should have an equal effect on the master template. It is noted that the feature representing the data is not restricted. It can be channel bank information, LPC parameters, line spectral pairs, etc.
To form the next frame, located at point (6,4), the horizontal move to point (5,4) must be taken. The weight assigned to this horizontal vector is accumulated to SOW. SOW becomes 2. Again, since SOW is limited to (mw+1), 2 is subtracted from SOW and SOW becomes 0. Hence, a frame is output at point (6,4).
A frame at point (5,4) is defined by traveling to (4,3) and adding the diagonal weight to SOW. SOW now becomes 2. Since SOW now equals (mw+1), no more weights can be added to SOW without exceeding its limit. A frame is output defined at point (5,4). Two is subtracted from SOW and SOW becomes 0.
Continuing along the path, the next frame is defined first by making a diagonal move to (3,2). The weight of 2 is added to SOW. SOW becomes 2. Since SOW is again at (mw+1), a frame is defined at point (4,3) and (mw+1) is subtracted from SOW. SOW again becomes 0.
The definition of the next frame is unique from the others. First the weight of the horizontal move to point (2,2) is added to SOW. SOW becomes 1. In this instance, SOW does not reach (mw+1) and another move is made. This move is the diagonal move to point (1,1), which requires a weight of 2 be added to the SOW. SOW now equals 3. Since 3 is greater than (mw+1), a frame is output defined by points (3,2) and (2,2), i.e. the output frame is defined by averaging the data represented by frames 2 and 3 from the new token and frame 2 of the master template. As after each other output frame, mw+1 is subtracted from SOW. SOW becomes 1.
The last frame defined in FIG. 3 entails updating SOW with a value of (mw+1)/2, or 1. To facilitate computation in actual practice, SOW is updated at (1,1) with the value (mw+1). This allows any partial output frames to be added into the last frame which is output, which in this case is (1,1). SOW becomes 2 with this move. Since SOW is at the (mw+1) threshold, a frame is output at point (1,1), and the averaging process is complete with the new master template defined by these 6 output frames.
This method for combining the new token with the master template is referred to as a backtracking process. This is because the averaging is done from the endpoint in time to the beginning point in time as defined by the frame sequence. The example of backtracking depicted through FIG. 3, is relatively simple. More complex examples occur when the number of frames on each axis is large and the master template consists of multiple tokens, i.e. mw is greater than 1.
FIG. 4 is a backtracking flowchart for averaging words as shown in the example of FIG. 3. It is a detailed illustration of block 26 from FIG. 1. Two key variables are used in this flowchart. They are NOBF and VS.
NOBF is a counter indicating the number of backtrack frames which are being considered for the current output frame. NOBF is reset to 1 during initialization and after each frame is output.
VS stands for vector sum and represents an accumulation of the weighted sum of the data representing the frames from the master template and the new token. It is used to accumulate the weighted frames from the master template and the new token. The feature data representing VS is normalized to generate an output frame. The normalization requires that each contributing frame be averaged according to the weight of the master template and the token. Mathematically, such averaging can be expressed as: ##EQU2## where A1, A2, . . , AN represent frames from the master template, and B1, B2, . . , BN represent frames from the token. Each divisional term in the numerator represents one point on the distance grid.
This expression can be simplified by factoring out (mw+1) as follows: e ##EQU3## Since each term is generated during the backtracking process, "mw" cannot be factored out from the numerator. This is because only one frame is pointed to at a time by (i,j).
The flowchart begins by initializing SOW, as discussed; setting VS to the weighted sum of the (new token frame I)+(mw * master template frame J); setting NOBF equal to 1; and defining the first point on the time alignment path (i,j) at (I,J). This is illustrated in block 40.
Block 42 depicts a move to the next most previous point on the path, and the weight of the move accumulates into SOW. Block 44 indicates a test to determine whether or not the move caused SOW to reach the normalization factor, (mw+1). If (mw+1) is not reached, block 46 increments the number of backtrack frames, NOBF, and block 48 updates VS to accumulate the information in frames (i,j). Block 42 is returned to for another move along the path.
If mw+1 is reached by SOW, block 44, a frame is output which is defined by the points on the path which have not already been included into an output frame. The output frame is the normalized vector sum given by [VS/[(mw+1) * NOBF]], shown in block 50. After the frame is output, a test checks whether or not all the points on the path have contributed to output frames, block 52. If they have, the procedure terminates.
If all the points on the path have not contributed to an output frame, the vector sum is initialized, block 54. NOBF is reset for the next output frame, block 56, and SOW is normalized by subtracting (mw+1), block 58.
The procedure continues at block 42 with a move along the time alignment path, until all the points on the path are included in an output frame.
Accordingly, each new token is averaged into the master template by time aligning the new token with the master template using dynamic programming, and averaging the new token with the master template onto an averaged time axis using the backtracking technique shown in FIG. 4. The final result of the averaging is a word template used for comparing against user spoken words in the recognition process.
FIG. 5 shows an example of this backtracking process using the flowchart in FIG. 4. The graph has weights assigned to the vectors as shown in the corresponding vector diagram. Two tokens have been averaged into the master template as seen on the vertical axis of the vector diagram. Table 1 is to be used in conjunction with the graph of FIG. 5. In Table 1 is recorded the variables used in the flowchart of FIG. 4 for averaging the two words shown on the graph of FIG. 5. On the left side of Table 1, a column indicates the corresponding block of the FIG. 4 flowchart for each variable assignment. By using this column, the example, as depicted in the graph 70 can be easily followed.
Table 1 begins at block 40 by initializing SOW, VS, NOBF and (i,j). The path is traveled along to point (10,8) and SOW is updated, block 42. Not shown in Table 1 is the test indicated by block 44, but the test decision is indicated by the NOBF update as seen in the next table entry, block 46. At this point, NOBF is incremented to 2 and VS is updated. Another move is made along the path, again indicated by block 42. Finally, since (mw+1) is reached by SOW, the first frame is output, frame #9. Blocks 54, 56 and 58 then update VS, NOBF and SOW respectively. Another move is made along the path, block 42.
The process continues until each point on the path contributes to an output frame, as was discussed with respect to the example of FIG. 3. The table can be followed in this manner for each frame which is output as circled in FIG. 5.
Referring now to FIG. 6, shown is a block diagram of a speech recognition system implementing the word template generation technique described herein. A microphone 70 is used to input spoken words. The analog speech is converted into digital representation using a feature extractor 72, such as the one described by G. M. White and R. B. Neely, "Speech recognition experiments with linear prediction, bandpass filtering, and dynamic programming," IEEE Trans. Acoust. , Speech Signal Processing, vol. ASSP-24, pp. 183-188, April 1976.
An endpoint detector 74 is employed to define the beginning and ending of the spoken word from the representative feature data. Such an endpoint detector is described in prior art by L. F. Lamel, L. R. Rabiner, A. E. Rosenburg, and J. G. Wilpon, in a paper entitled "An improved endpoint detector for isolated word recognition," IEEE Trans. Acoust. , Speech Signal Processing, vol. ASSP-29, pp. 777-785, August 1981.
The endpoint detector 74 defines a token for storage as shown in block 76. The master template is initially defined from a single token. Thus, the endpoint detector 74 stores an initial token in memory block 78 as well. Memory blocks 76 and 78 are typically RAM.
A dynamic time warping processor 80 aligns the master template, stored in memory block 78, with the token, stored in memory block 76. A detailed description of dynamic time warping requirements is described by Sakoe and Chiba, supra. A backtracking processor 82 is be used to process the corresponding token data with the master template data according to FIG. 4. A Motorola type 6805 microprocessor can be used for this purpose. The resultant master template is stored back in master template memory, block 78.
After averaging is completed, the resultant master template is stored in template memory 84. The template memory employed can be RAM, non-volatile RAM or EEPROM.
Words are averaged in this manner until the template memory contains the appropriate vocabulary for the speech recognition process. For a detailed description of a recognizer 86, reference the paper by F. Itakura, "Minimum prediction residual principle applied to speech recognition," IEEE Trans. Acoust. , Speech, Signal Processing, vol. ASSP-23, pp. 67-72, February 1975.
Accordingly, by using a template generation method as described herein, a very accurate word template can be generated and utilized in a speech recognition system. The generated word template is not only highly reliable for use in the recognition process, but it is equally representative of each word spoken during word training.
TABLE 1______________________________________BLOCK SOW (i,j) NOBF OUTPUT FRAME______________________________________40 11/2 (11,8) 142 21/2 (10,8)46 24842 51/2 (9,7)50 #9: (11,8), (10,8) = VS/2(2 + 1)54,56,58 21/2 142 31/2 (8,7)50 #8: (9,7) = VS/(2 + 1)54,56,58 1/2 142 31/2 (7,6)50 #7: (8,7) = VS/(2 + 1)54,56,58 1/2 142 31/2 (6,5)50 #6: (7,6) = VS/(2 + 1)54,56,58 1/2 142 11/2 (5,5)46 24842 41/2 (4,4)50 #5: (6,5),(5,5) = VS/2(2 + 1)54,56,58 11/2 142 21/2 (3,4)46 24842 51/2 (2,3)50 #4: (4,4),(3,4) = VS/2(2 + 1)54,56,58 21/2 142 41/2 (2,2)50 #3: (2,3) = VS/(2 + 1)54,56,58 11/2 142 41/2 (1,1)50 #2: (2,2) = VS/(2 + 1)54,56,58 11/2 142 41/2* (0,0)50 #1: (1,1) = VS/(2 + 1)______________________________________ *(mw + 1) is added for the last diagonal move to allow any partial frames to be rounded into the frame at (1,1).
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|Dec 14, 1990
|Oct 29, 1991
|Matsushita Electric Industrial Co., Ltd.
|Method and apparatus for speech recognition
|Nov 2, 1989
|Dec 10, 1991
|International Business Machines Corporation
|Automatic determination of labels and Markov word models in a speech recognition system
|May 22, 1990
|Nov 17, 1992
|Alcatel N.V.
|Method and apparatus for recognizing unknown spoken words and by feature extraction and comparison with reference words
|Apr 24, 1992
|Aug 3, 1993
|International Business Machines Corporation
|Context-dependent speech recognizer using estimated next word context
|Dec 5, 1991
|Jan 11, 1994
|International Business Machines Corporation
|Speech coding apparatus having speaker dependent prototypes generated from nonuser reference data
|Jan 21, 1994
|Dec 27, 1994
|At&T Corp.
|Technique for modifying reference vector quantized speech feature signals
|Nov 13, 1992
|Jun 27, 1995
|Dragon Systems, Inc.
|Apparatus and methods for training speech recognition systems and their users and otherwise improving speech recognition performance
|Apr 14, 1994
|Jan 30, 1996
|Northern Telecom Limited
|Method and apparatus for training speech recognition algorithms for directory assistance applications
|Jul 7, 1994
|Dec 3, 1996
|Sharp Kabushiki Kaisha
|Learning dynamic programming
|May 25, 1995
|Jul 1, 1997
|Northern Telecom Limited
|Updating markov models based on speech input and additional information for automated telephone directory assistance
|May 12, 1993
|Sep 2, 1997
|Nynex Science & Technology
|Method of training a speaker-dependent speech recognizer with automated supervision of training sufficiency
|May 3, 1995
|Jan 6, 1998
|Assefa; Eskinder
|Method and apparatus for compressing and decompressing voice signals, that includes a predetermined set of syllabic sounds capable of representing all possible syllabic sounds
|Nov 29, 1996
|Nov 17, 1998
|Northern Telecom Limited
|Method and apparatus for automatically generating a speech recognition vocabulary from a white pages listing
|Apr 14, 1995
|Dec 1, 1998
|Industrial Technology Research Institute
|Endpoint detection in a stand-alone real-time voice recognition system
|Jun 26, 1997
|Dec 15, 1998
|Dragon Systems, Inc.
|Apparatuses and methods for training and operating speech recognition systems
|Jun 26, 1997
|Jun 1, 1999
|Dragon Systems, Inc.
|Speech recognition system which creates acoustic models by concatenating acoustic models of individual words
|Jun 26, 1997
|Jun 22, 1999
|Dragon Systems, Inc.
|Word recognition system which alters code executed as a function of available computational resources
|Jun 26, 1997
|Jul 6, 1999
|Dragon Systems, Inc.
|Word recognition system using language context at current cursor position to affect recognition probabilities
|Jun 26, 1997
|Jul 6, 1999
|Dragon Systems, Inc.
|Word recognition system which stores two models for some words and allows selective deletion of one such model
|Feb 6, 1997
|Sep 28, 1999
|Canon Kabushiki Kaisha
|Pattern matching method, apparatus and computer readable memory medium for speech recognition using dynamic programming
|Dec 18, 1997
|Nov 9, 1999
|Nortel Networks Corporation
|Method and apparatus for obtaining transcriptions from multiple training utterances
|Jun 26, 1997
|Nov 9, 1999
|Dragon Systems, Inc.
|Speech recognition system which turns its voice response on for confirmation when it has been turned off without confirmation
|Dec 16, 1996
|Nov 16, 1999
|Nortel Networks Corporation
|Automated directory assistance system utilizing a heuristics model for predicting the most likely requested number
|Oct 31, 1996
|Nov 16, 1999
|Nortel Networks Corporation
|Method and apparatus for selecting a vocabulary sub-set from a speech recognition dictionary for use in real time automated directory assistance
|Sep 12, 1997
|Nov 30, 1999
|Nortel Networks Corporation
|Method and apparatus for generating an a priori advisor for a speech recognition dictionary
|Aug 26, 1997
|Jan 25, 2000
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|Sep 19, 2000
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|Mar 27, 2001
|Nortel Networks Limited
|Method and apparatus for providing unsupervised adaptation of transcriptions
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|Method and apparatus for obtaining a transcription of phrases through text and spoken utterances
|Oct 20, 1997
|Jun 26, 2001
|Nortel Networks Corporation
|Split-vector quantization for speech signal involving out-of-sequence regrouping of sub-vectors
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|Nec Corporation
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|Jan 4, 2005
|Harman Becker Automotive Systems Gmbh
|Process for automatic control of one or more devices by voice commands or by real-time voice dialog and apparatus for carrying out this process
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|Recovering an erased voice frame with time warping
|Jul 26, 1999
|Jun 13, 2006
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|Apparatus, method and computer readable memory medium for speech recognition using dynamic programming
|Oct 1, 2002
|Jul 8, 2008
|Siemens Atkiengesellschaft
|Method for producing reference segments describing voice modules and method for modeling voice units of a spoken test model
|Oct 8, 2009
|Mar 10, 2015
|Mitsubishi Electric Corporation
|Voice recognition system for registration of stable utterances
|Jul 26, 1999
|Mar 14, 2002
|Eli Tzirkel-Hancock
|Apparatus, method and computer readable memory medium for speech recogniton using dynamic programming
|Mar 11, 2004
|Sep 16, 2004
|Mindspeed Technologies, Inc.
|Recovering an erased voice frame with time warping
|Oct 1, 2002
|Dec 9, 2004
|Bernhard Kammerer
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|Feb 20, 2004
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|Curitel Communications, Inc.
|Mobile communication terminal having voice recognition function, and phoneme modeling method and voice recognition method for the same
|Oct 15, 1990
|Apr 24, 1991
|Logica Uk Limited
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|Apr 16, 1992
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|Jul 15, 1993
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|Voice recognition apparatus and method
|Sep 9, 1996
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|U.S. Classification
|International Classification
|Cooperative Classification
|European Classification
|Nov 6, 1985
Owner name: MOTOROLA, INC., SCHAUMBURG, ILLINOIS, A CORP. OF D
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST.;ASSIGNORS:GERSON, IRA A.;LINDSLEY, BREET L.;REEL/FRAME:004482/0177
Effective date: 19851104
|Jan 14, 1992
|Maintenance fee reminder mailed
|Jan 22, 1992
|Fee payment
Year of fee payment: 4
|Jan 22, 1992
|Surcharge for late payment
|Aug 7, 1995
|Fee payment
Year of fee payment: 8
|Sep 23, 1999
|Fee payment
Year of fee payment: 12


text:
It's hard to know what to make of this story. Did the fellow who had the table saw accident regrow a substantial part of his finger or was it just the tip? Whatever it was, I congratulate him on his recovery but not on his relapse into dangerous work practices.
I understand why flooring installers free-hand cut on the table saw (it's so they can quickly make tapered pieces), but really – do you have to put your fingers that close to the blade? And what's with the squinting and not wearing safety glasses? That "miracle powder" may work for fingers – but no one said it can regenerate eyeballs.
Watch the video and you'll see what I'm talking about. Feel free to comment.
The introduction and development of power tools so completely transformed construction...
An attorney weighs in on the potential fallout from last week's ruling regarding...
The Stihl battery-powered TSA 230 Cutquik cut-off machine changes the game for the...
Table Saws
25 favorites from the outgoing editor.
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If Ron Paulk's original portable workbench was excellent (and it was), then this new...
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Two well-known power tool companies prepare to duke it out in the parking lot.
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subset: commoncrawl


text:
Mow your lawn with greater ease by purchasing a new lawnmower from Nailsworth Garden Machinery.
Keep your equipment in good working order by taking advantage of our availability to service and repair your garden tools.
When your garden equipment has had a good run, there are always parts that need replacing. Contact our team, because we
can help you.
Take advantage of our offers, including 10% discount off ALL petrol machines serviced before the end of March 2015!
An independent, family-run business, Nailsworth Garden Machinery has over 50 years of experience in sales, servicing and repairs of garden machinery from a range of different makes and models. We pride ourselves on the quality of our service and offer expert advice with a smile!
Please our Special Offers Page for Current Promotions.


text:
60 steps to sandy ocean beach across the street.
|Per week:
|$1,700 - $2,500
|Pets allowed:
Bedrooms: 6
Bathrooms: 3
Sleeps: 14
Type: Home
Pets allowed: No
Internet: Yes
Peak season: June 5 - Sept 9
$1700/week front house 3br 1 ba outdoor shower
$2500/week rear house 3br 2 bath outdoor shower
$4000/week both 6br 3 ba 2 outdoor showers
off season:Sept 12-Oct 30
Front house:1050/week 700/weekend
Rear house: 1250/week 900/weekend
Rentals are Sunday-Sunday
About the owner
Owner Profile
Availability Calendar
|Jun 19 2016
|Sep 05 2016
|1 Week
|Jun 19 2016
|Sep 05 2016
|1 Week
|Check In: 3 p.m. Check Out: 11 a.m.
|Deposits: 50% due at time of booking, remainder or 50% due 30 days before stay
|Payment Options: American Express, Cashier's Check, Discover, Mastercard, Money Order, PayPal, Personal Check, Visa
|Other Fees: $200 security per house
- 1 Queen Bed
- 3 Double Beds
- 6 Twin Beds
- Air Conditioning
- Full Kitchen
- High Speed Internet
- Patio
- Beach Chairs
- Hardwood Floors
- Outdoor Shower
- View (Ocean)
- Deck
- Heating
- Parking Included
- Ceiling Fan
- Microwave
- Stove
- Toaster
- Coffee Maker
- Oven
- TV (Cable/Satellite)
- Washer/Dryer
- Gas Grill
- Refrigerator (Full)
- Beach
- Surfing
- Kayaking
(<1 mile)
- Scuba Diving
(<1 mile)
- Bicycling
- Amusement Park
(<1 mile)
- Miniature Golf
(<1 mile)
- Shopping Area
(<1 mile)
- Boating
- Canoeing
(<1 mile)
- Parasailing
(<1 mile)
- Snorkeling
(<1 mile)
- Fishing
- Deep Sea Fishing
(<1 mile)
- Restaurant
(<1 mile)
- Whale Watching
(1 mile)
- Ocean
- Jet Skiing
(<1 mile)
- Sailing
(<1 mile)
Reviews (7)
Reviews for this vacation home rental in Dennis Port, Massachusetts
Marc Nantel
Weymoth,Ma USA
Better tha expected
September 10, 2015
this house is like on a compound. another house is in the same yard. Great for family get together. It is a cottage, no super frills, but that is why you go to the cape. To be near the water. Super friendly owner, very accommodating. She will fix any issues. the whole family thought it was great. Steps from the beach. Expect t come back again soon.Super nice to have a washer and dryer in the house. Great memories for the faily.
Laura Zabek
Our FAVORITE!
August 25, 2014
We stayed last year in the front house, and were sure to book it again this summer. Equally as enjoyable, and are totally looking forward to staying again next year. Terri is wonderful; home is in a perfect location; couldn't ask for more! A great value!!!!
Cathy J Cairns
Monroe, New York, USA
1st attempt at a Family Reunion
June 30, 2014
What a perfect place for a family reunion! We rented 73 front and 73 rear as well as 69 front. There was more than enough room for all the famiilies involved and the seperate spaces ensured your privacy when togetherness got to be to much! The 3 homes were all clean, in good repair and surprisingly spacious. Short walk to the beach was do-able even for the older members. Beach was clean and waters calm enough for the youngest! We were there before busy season and the beach was relativley empty. Owner Terri was very helpfull throughout this whole process...no matter how many time I emailedor texted her! I am glad we chose these 3 houses for our vacation!
Ryan Callahan
South Boston, MA
Book It Now!!
July 2, 2013
I reserved this property for a "reunion" of friends from college during a weekend in June and could not have been happier. Upon entry into the property I immediately noticed how well furnished and clean the house was. Look out the windows down the street and you can see the beach, only a short walk away. Each house on the property was complete with a TV (with cable), more beds than you could ever imagine and a large outdoor grill with a full tank of propane. I highly reccomend this property to anyone that is planning a larger family/friend get together and wants to pay a very fair price for a great property. We are already planning on booking it again next year!
Kathleen Colligan
Nice family location
August 31, 2012
Our family had a wonderful time renting both of these houses for our family. The house was clean and located close to the beach, ice cram stand and convenience store. Renting it with the owner was a pleasure .
Thomas Gochis
beach people
July 18, 2012
We have been vacationing on the cape for about 15 years and each year we try to get closer to the beach. We stayed here and it was fantastic, short walk to the beach(60 seconds), very roomy and comfortable and clean. it was the first year I don't think anyone complained(and if you have teenage girls you know what it mean) the owners were very accommodating would defiantly come back and recommend
Diana deLeo
Thomaston, CT USA
All-in-All we Enjoyed ourselves.
July 29, 2011
Enjoyed our stay at 73 Ocean Drive ,there were a few issues that need be addressed #1 the kitchen sink leaked constantly leaving a mold and mildewy smell under the sink #2 the down stairs shower nob fell off almost hitting people's feet causing a hazard conditions.#3 refridge did not keep food cold. The things we did enjoy- the size of the house was very accommodating, closeness of the beach to the home, house in the rear made it safe for children playing outside not close to the street . Our family would highly consider rent home again next summer. Thanks.
Owner's reply:
Diana is returning this year. We did repair all problems. As owners we are given the opportunity to allow reviews to post or not. We felt all reviews should be posted, even if something negative is said. Apparently the sink was leaking for 1 1/2 weeks without our knowledge. As soon as Dianne informed us of the leak we sent a plumber to replace the faucet (faucet and shower were only a year old- things are made so cheaply these days) Refrigerator needed to be defrosted. ice was blocking the fan. As soon as we are informed of a problem, we immediately take care of it. Just as in our own homes, problems do arise in a rental house, even more so since different groups of people are renting each week that are unfamiliar with the systems of the house.
Write a review!
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text:
Key things you need to know aboutDr. Skupski:
Phone & Address
Check insurance plans, locations and make an appointment
Accepting new patients?
- Yes
Dr. Skupski's Offices
(212) 235-1496
- (212) 746-3045
- Directions
- New York Weill Cornell Med Ctr
- New York Weill Cornell Med Ctr
- 525 E 68th St Ste M701
- New York, NY 10065
(212) 235-1496
- (212) 746-3069
- Directions
7 Tips to Prepare for Your Appointment
The key to a successful appointment is communication. To get the most out of your visit, prepare ahead of time so you can lead the conversation with your doctor. These 7 tips will get you ready
Dr. Skupski's Experience
Research training, expertise and qualifications
Dr. Skupski's Specialties
- Maternal-Fetal Medicine
- View all 2 Specialties and 2 board certifications
Conditions Dr. Skupski Treats
- Abdominal Disorders
- Antiphospholipid Syndrome (APS)
- See all 55 conditions
More About Dr. Skupski's Background
Hospital Quality
The right hospital is as important as the right doctor
- NewYork-Presbyterian/Weill Cornell Medical Center
- 525 E 68th St
- New York, NY 10065
- Lincoln Medical and Mental Health Center
- 234 E 149th St
- Bronx, NY 10451
9 Facts About Hospital Quality
Patients' risk of dying during a hospital stay for heart bypass surgery could be 87.4% lower, on average, at a hospital rated 5 stars compared to a hospital rated 1 star for that procedure. Choosing the right hospital is critical to your health. View Slideshow
Patient Satisfaction
Patients' feedback on their experience with Dr. Skupski
Likelihood of recommending Dr. Skupski to family and friends is 5 out of 5 5 1 3
See More Survey Results
8 Facts About Patient Satisfaction Surveys
Patient satisfaction surveys provide a standardized way of reporting about healthcare experiences. But there can be more than meets the eye when reviewing scores. Here's what you should know
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text:
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Order Your Waring Commercial Parts & Accessories Today!
This WCG502TX Grinding Blade is for use with the Waring Commercial Chopper/Grinder Model Number WCG75. Use this Grinding Blade in conjunction with the Grinding Bowl and Cover Model Number WCG506TX.
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text:
Students with Asperger Syndrome have a difficult time attending class. They react even worse when transferred to a different school. One parent says that's exactly what her son has been forced to do.
For nearly a decade, Andrew Valenti, 13, has walked the halls of Father Marquette Catholic schools. Now he's pacing the sidewalk for his right to stay there.
"I was pretty much kicked out for something that I can't help," said Andrew.
Last April, Andrew's doctors diagnosed him with Asperger Syndrome, a form of autism with difficulties in learning and social skills.
"He has a lack of focus, his organizational skills are very hard, and he doesn't pay attention a lot in class," said Heather Milliner, Andrew's mother.
Everything seemed OK. The middle school has at least 20 other students with special needs. Last fall they hired their first special education teacher.
"I thought, great, maybe Andrew will improve and his grades will improve," Milliner said.
But that didn't happen. Last January, officials sent letters to Andrew's parents stating the school simply isn't equipped to handle his disability.
"Sometimes the services that are provided through those means are not as direct as we would like them to be; that's when we have to look at the sacrifice, trying to get the resources to provide more direct service," said Superintendent Mark Salisbury.
Andrew is currently at North Star Academy in Marquette, but family members say the fight isn't over.
"I want them to reevaluate their resources and make sure they have it in place before they accept new students," said Chris Valenti, Andrew's father.
The Diocese of Marquette says they are looking to prevent this problem in the future by outlining their limitations during the application process.


text:
Ghost Peloton Glasgow: tickets on sale now
Ghost Peloton comes to Glasgow
#summertime is starting! #Kilmahew/St Peter's
NVA is a registered Scottish charity and company limited by guarantee. Our operational costs are funded primarily through self-generated income and Creative Scotland's Regularly Funded Organisations programme. Our artworks are funded through a range of public and private sources and generous public donations. One hundred percent of these funds are invested directly in achieving our charitable objectives which are to advance education through the promotion of culture and the arts, to protect natural landscapes and heritage and to promote for the public benefit the preservation of buildings and other structures of historical or architectural significance. Scottish Charity No. SC027613.


text:
Recipes using Brown sugar
Strawberry Salad
Golden Delights Who: Fairview Haven Retirement CommunityCost: $25 includes shippingDetails: soft-backed, spiral boundPages of recipes: 331Send checks to: Fairview Haven Retirement Community, Attn: Sally, 605 N. Fourth St., Fairbury, IL 61739 or call 815-692-2572.
Oven Baked Praline French Toast
Recipes from the Parish Who: Wesbein and Cropsey United Methodist ChurchesCost: $16 includes shippingDetails: soft-backed, spiral boundPages of recipes: 137Send checks to: Susan Wright, 36681 E. 1000 N Rd., Saybrook, IL 61770 or call 309-475-9080.
Peanut Butter Pumpkin Dip
Finest Cooking Holiday Recipe Contest Submitted by: Christine Mize, Egyptian Electric Cooperative Association
Twice Baked Sweet Potatoes
Recipes from Our Parishioners, Past and Present Who: St. Mary of the Assumption ChurchCost: $17 includes shippingDetails: hard-backed, 3-ring boundPages of recipes: 158Send checks to: Judith Wagner, St. Mary of the Assumption Church, 112 W. Embarrass St., P.O. Box 68, Sainte Marie, IL 62459or call 618-455-3155
Healthy Breakfast Muffins
The Goose Supper Cookbook Who: Lynnville Christian ChurchCost: $21.50 includes shippingDetails: soft-backed, spiral boundPages of recipes: 248Send checks to: Jack McNeely, Lynnville Christian Church, 32 Albion Street, Lynnville, IL 62650or call 217-243-1687
Caramel Pecan Rolls
Recipes & Remembrances Who: St. Mary's Altar SodalityCost: $10 includes shippingDetails: soft-backed, comb boundPages of recipes: 155Send checks to: Joan Derringer,7781 Oakdale Road, Ellis Grove, IL 62241or call 618-534-6697
Apple Salsa with Cinnamon Chips
Nourishment For Our Body & Soul Who: Trinity Lutheran ChurchCost: $16 includes shippingDetails: soft-backed, spiral boundPages of recipes: 176Send checks to: Trinity Lutheran Church, c/o Megan Busacker, 402 N. Monroe St., P.O. Box 207, Harvel, IL 62538 or call 217-229-3143
Chocolate Chip Pie
Recipes from the Heart Who: The Lighthouse Shelter For The Homeless, Marion, ILCost: $13 including shippingDetails: soft-backed, comb-boundPages of recipes: 239Send checks to: The Lighthouse Shelter, 1101 N. Madison, Marion, IL 62959or call 618-964-1663.
Iced Cream Crunch
Saybrook Christian Church 2010 – Celebrating 150 Years Who: Saybrook Christian ChurchCost: $12, including shippingDetails: soft-backed, comb-boundPages of recipes: 123Send checks to: Linda Beatty, 40187 E. 1150 N. Rd., Saybrook, IL 61770 or call 309-475-8241.
Winter Squash Chowder
Featuring specialty crop recipes This recipe courtesy of The Pumpkin Eater – 2nd Edition, The Great Pumpkin Patch, www.the200acres.com or 217-543-2394.


text:
A Tribute to the Sun of His Heart's Setting
The cats and dogs pouncing
On the rooftop have come and gone,
Leaving a hazy cirrus stripe
Outside the dusty windowpane.
Peeking, I see through the Earth's soupy steam
An old man I once knew well
Still casting his pole onto the lake's wet skin,
Overalls and the willow he wears
Soaked to the core for he has sat
In his paint-flaking rowboat on the nose of the lake
Since before I was to awake.
I wonder what he thinks about
In his boat every dawn until break,
Sitting still as a statue, his eyes staring
As the bobber floats around
In the blue-green pool of tears.
His light pink fishing hat,
A pop of color in nature's shades,
Continue Reading »


text:
Genre: Crime
Premise: This true-crime series begins each episode with a shocking event -- an unexplained disappearance, a cold-blooded killing, a violent assault. As the investigation into the crime unfolds, a strong woman with a connection to the victim, or an ambitious prosecutor, decides to stay on the case until the crime is solved.
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text:
Spanking: Abuse or discipline?
katie 2012/02/11 00:10:09
Top Opinion
More polls by katie
Sort By
- Julian O'Leary 2012/08/15 05:25:49
- AndyBoy 2012/08/03 16:26:56
- American☆Atheist 2012/07/05 06:20:29
- Roy Mun... America... 2012/07/29 22:18:15no it dosen't
- America... Roy Mun... 2012/07/29 23:38:43
- Roy Mun... America... 2012/08/01 01:10:51so i must be mentally ill w/e
- America... Roy Mun... 2012/08/01 20:49:15
- Roy Mun... America... 2012/08/01 02:38:41here,read this http://www.periscopepost.com/...
- America... Roy Mun... 2012/08/01 20:48:43
- Vitalani 2012/05/02 20:27:34
- Roy Mun... Vitalani 2012/07/29 22:20:49easy way out? back in the y,children respected their elders,now look at the schools and disrespect these days,what's your idea? a time out?
- Vitalani Roy Mun... 2012/07/31 08:24:53I have many very effective ideas, which I have used for the past few years quite effectively. Time outs scare the children I raised much more than a spanking. So did losing their toys or not getting to go to a friends house.
- Roy Mun... Vitalani 2012/08/01 01:18:55oh god...here we go with the time outs again,so what do you think should happen to people who spank their children? jail time?
- Vitalani Roy Mun... 2012/08/02 19:39:40+1Don't put words in my mouth. Making things up just makes yourself look like a moron. Same as the 3 separate replies. Bravo. And no, tone of voice is in no way verbal abuse, as it does not even fit the definition. However hitting DOES fit with physical assault.
*helping* to raise a child is not the same as raising one. It does not even compare.
- Roy Mun... Vitalani 2012/08/01 01:20:31i helped raise a little girl and i only spanked her a couple of times and after i did that i held her and explained why i did it and she turned out perfectly fine
- Roy Mun... Vitalani 2012/08/01 01:23:33and i suppose raising your voice or talking stern to them is verbal abuse?
- pdarkow 2012/05/02 11:05:21
- Roy Mun... pdarkow 2012/07/29 22:21:00
- Hot Wheels 2012/05/02 06:17:32 (edited)
- Lydecho Rain (Лидия) 2012/03/22 23:04:35
- Hot Wheels Lydecho... 2012/05/03 22:28:41
- Lydecho... Hot Wheels 2012/05/04 23:57:17It's not discipline. It's not exactly horrible, but honestly it's not effective. I wouldn't care at all if my parents spanked me, but when they actually took away my ipod or something like that I would start to behave better. I know some kids that got spanked and they're worse behaved than anyone else. Honestly, if people want to hurt their kids to punish them that's just stupid and ineffective anyways.
- Roy Mun... Lydecho... 2012/07/29 22:21:22
- Hot Wheels Roy Mun... 2012/12/18 16:30:27AMEN!
- Roy Mun... Lydecho... 2012/08/01 01:21:17
- Fran-Halen 2012/02/11 20:12:25
- Nuzz 2012/02/11 19:12:01
- GoDucks5 2012/02/11 04:03:59
- Reggie☮ 2012/02/11 00:47:52
- Hot Wheels Reggie☮ 2012/05/02 06:19:15
- trigger2fish 2012/02/11 00:47:09
- Doug King 2012/02/11 00:28:07
- Umbreon! 2012/02/11 00:26:22
- Truth H... Umbreon! 2012/06/08 03:48:02So you are telling me that a teenager doesn't know right from wrong?!?!?!?!?!?!?!? Come on.
- Umbreon! Truth H... 2012/07/03 14:07:46No, a lot of the times, they don't.
- Kari 2012/02/11 00:19:25
- Kyle 2012/02/11 00:14:31
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This column from The Portland Tribune chews out the city's "light-rail mafia" and claims that the only people benefiting from Portland's elaborate transit plans are the power players making the decisions and their developer friends.
"When you get right down to it, just who do all these expensive light-rail lines, aerial trams, high-rise condo developments and proposed convention-center hotels really benefit?"
"If you want to know the answer to that, as good of a place as any to start is a new book by local antiplanning guru Randal O'Toole called 'The Best-Laid Plans.'"
"As O'Toole sees it, the whole planning process has been taken over by a 'light-rail mafia' – which has managed 'to direct rail construction contracts and urban-renewal subsidies to themselves.'"


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B2B's social media superstars
Nov 4th
Success stories in this space are few and far between. A recent report showed just 14% of the largest industrial companies have a social media strategy, let alone a good one. There are many good reasons for the slow adoption of SM at the industrials, including the perilous economy and a customer base that could care less about your freakin' tweets if their railcar of chemicals is an hour late.
A few months ago I spent time assessing the state of SM at B2B companies and overall, my research showed that B2B companies don't seem to get the notion of community and are trying to fit traditional marketing stereotypes into the new media. Here are five breaking the mold and leading the way:
Number 5: Ingram Micro — Ingram Micro is the world's largest technology distributor to the IT industry. You would think with a geek-fest customer base they would have all of the sweetest social media apps – and they probably do, behind a secure firewall where it belongs! Ingram makes the list for the very cool open Facebook sites connecting employees among its far-flung global operations. Recently used Twitter to "broadcast" from a partners meeting.
Number 4: Boeing — The time-lapse YouTube videos of planes being built are impressive but the cornerstone of Boeing's social media presence is a longtime blog, started by their VP -Marketing Commercial Airplanes, as a way to expand the conversation of commercial aviation to the Web. In its first two years, Randy's Journal, saw more than a half million individual visits. They have a secure presence on Twitter. Any good? Don't know — I wasn't allowed through the gate. Let me in! I have an appointment to see the wizard!
Number 3: Cisco Systems — Extraordinarily good community-building on Facebook, including a blog, message board, news and open membership for employee sites around the world. Proving to be a real B2B social media innovator as they launch products only on digital channels. They even launched a product through Second Life. I don't know if anybody actually saw it, but they did it.
Number 2: General Electric — I've found that when a company is well-managed, it tends to do EVERYTHING well. GE is no exception. They have a thoughtful, integrated social media presence that is informative, professional and … fun. GE distinguishes itself as the only leading industrial company that places an actual face with its SM efforts — Megan Parker. She effectively mixes effective press release reporting with 140-character wit. The real hub of the SM wheel is GEreports.com, a blog-style information center making effective use of videos and search-by-topic capabilities. You have to love a company that has a post on its Facebook page titled "I'm over 30 and still think it's OKAY to get hammered from time 2 time!!"
Number 1: IBM — For years their print and TV ads have puzzled me, but they seem to be getting social media right. IBM is a great example of a company with a real interest in community – a logical move since their tech audience loves online forums and bulletin boards. Check out their blog for proof of that. In fact, the IBM corporate social media presence is minimal as they let customers and employees tell their story. They've created the conversation and then they've let go of it. IBM's social media portfolio includes virtual worlds, podcasts, video and the use of Twitter to keep its 380,000 employees (in 150 countries) connected.
B2B's biggest social media screw-ups
Nov 3rd
While the case for social media as a marketing channel is compelling for consumer products companies, I've been particularly interested in how it is being used … or not … by mainstream industrials. Earlier this year I assessed the social media presence of most of the major Fortune 500 B2B giants looking for case studies.
I found some great examples, but for fun, I've decided to start out with the WORST companies I found out there. With few exceptions, major industrial companies are not utilizing – and in many cases ignoring — social media as a stakeholder connection point. A few fun facts:
- Number of Top 25 B2B companies with more Twitter followers than me (None)
- Worst B2B corporate Twitter-er (by far) — DuPont. An example: "Back off weeds! 4 new herbicides are coming to get you …"
- Most popular corporate social media platform: Facebook
- Percent of companies with either Facebook or MySpace pages: 75%
- Percentage with both: 25%
- Most popular use of social media: A place to post press releases
With no further delay, let's take a look at the Top Five biggest B2B social media screw-ups.
5. 3M Corporation – I love 3M. I've always cherished their heritage of innovation and product development. If any company in America could take advantage of the awesome power of global community it should be 3M. Where are you guys? We need you out here.
4. General Dynamics — There is a not-very-good techno rock band called General Dynamics who dominates the social media bandwidth. That's a problem for a Fortune 100 company with the same name. This is the time for the company to flex some legal muscle and tell them they were there first! In the corporate world, this ID theft is tantamount to a porn starlet naming herself "Pepsi." You have to take action on this, General Dynamics! Go kick some techno butt!
3. Oracle Corporation – You would expect an ego-laden company like Oracle to be sucking up the social media space, but not so. The Twitter account is exclusively a press release machine and their other sites are ill-attended placeholders. Larry, look at what SAP is doing with social media. Work it baby.
2. Johnson Controls — This Fortune 50 titan has had their name usurped on Facebook by a bunch of disgruntled employees. An example of social media gone very wrong when you're asleep at the wheel.
1. Dow Chemical Company. The pinnacle of social media mayhem. The first search result for Dow on Twitter is called "spillspill" and the largest company-related Facebook page is called Fuck Chemical Valley and Fuck Dow (42 members). The MySpace presence has also been hijacked, complete with fake logos, fake employees and a mission statement that includes: "minimizing damage by angry citizens who have been affected by our pollution through legal suits and PR campaigns, making sure scientists who find our products to be dangerously toxic are not allowed to publish." Dow has a proud history of PR fubars. The legacy continues.
Disclosure: My ex-wife had family ties to the chemical industry. While clinical tests have shown she is toxic to humans, she is not associated with the Fuck Dow campaign.
How do I get my boss to understand social media?
Nov 2nd
NEWS FLASH: If you are not being supported by your boss and you hope to pressure him/her into supporting your nascent social media initiative through a "grassroots" effort, it's not going to work. Not in the long run. For effective, lasting organizational change to occur, it must be supported from the top. How do you gain that support when your boss doesn't get it?
Who is the "sponsor" of your social media effort?
Here are six ideas to get the boss on-board:
Conduct a "pilot" program. One of the most effective ways to get something started is to propose a temporary project. For example, go to your boss and tell her you want to try a new idea for 12 weeks (which sounds shorter than 3 months!). Explain that you will do this as an added, incremental effort that will not interfere with your normal job duties, you will measure and re-evaluate at the end of the period, and together you'll decide whether to continue or not. Once the effort gets going and gains momentum, it's going to be difficult to stop unless you completely blow it. So don't blow it. : )
Money really does talk. Whatever you do, don't go into a meeting with a company executive explaining that you want sponsorship to measure your company's "quality of conversations." If you are still buying into the "it's all about the conversation" hype, read this (measurement and ROI) and this (focus on money). Of course the social web is about relationships, but everything measured in an organization SOMEHOW relates back to money, whether it's profits, donors or funding. Social media is no different. Be prepared to explain how your initiative ties to the company's objectives. If you can't, you're not ready for this discussion.
Preach fear in the morning and redemption in the afternoon. Scare 'em. Seriously. Fear is a great motivator: Fear of what the competition is doing, fear of being left behind, fear of missing a trend, fear of making a wrong decision. Then, after your boss is shaking in his boots, explain what you can do to beat the competition, keep your company ahead, and make your boss look great … for absolutely no investment!
Plan for problems. When implementing change in an organization, it's important to have a counter-measure for every obstacle you're likely to face. Literally write down every possible argument and reason people will argue against your social media proposal and then formulate a reasonable counter measure to address them. And the hurdles aren't just money and resources. It could be politics and competing priorities. Get your supporters to help you think-through effective answers to anything your boss can throw at you and be well-prepared.
Where's your truckstop?
Oct 30th
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Poll: Puerto Rico 51st State?
By a slim majority, Puerto Ricans have voted to become the 51st U.S. state. Tuesday's non-binding referendum requires final approval from Congress.
President Barack Obama earlier expressed support for the referendum and pledged to respect the will of the people in the event of a clear majority.
Tonight in the Daily Pulse we're wondering: Would you support Puerto Rico becoming the 51st state? Yes or no? Why or why not?


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Firefighters stopped flames from the white transit van reaching vehicles belonging to bus company Transdev Keighley and District.
The van, which was set alight around 10.30pm, was in a fenced-off car park at Keighley Plumbers Merchants in Chapel Street.
Watch commander Mark Collingwood, from Keighley fire station, said it was unlikely the flames would have spread to the buses.
But he said: "If we'd got it 10 or 15 minutes later when the whole van was alight possibly it could have damaged the buses.
"We think the likelihood is that the fire was malicious."
A car parked next to the van suffered smoke damage.
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60D Shutter Speed Stuck - help me diagnose?
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Going to update firmware today just in case. Yes, this persists in manual mode (these pictures were taken in manual mode and purposefully only shutter speed was changed). It also persists in automatic and tv (in automatic, shutter speeds just set super slow regardless of lighting situation). I can keep pictures from blowing out in bright light only with super deep DOFs.
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The Pelicans Jazz Up The Pick And Roll, Joel Freeland Gets Baptized
The New Orleans Pelicans like to run pick-and-rolls a lot. In fact, through their 29 games so far this season, they've used it in 35.3 percent of their offensive sets because it's been that good to them. A lot of that has to do with the fact that they acquired the pick-and-roll fiend that is Jrue Holiday in the off-season. Continue Reading


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Thread: Bob McGinn Draft Series: Offensive Linemen
-05-03-2014 #1
Bob McGinn Draft Series: Offensive Linemen
Auburn tackle Greg Robinson stands out in talented lineman class
Bob McGinn | On the Packers
Green Bay Devotees of magnificent offensive line play have been waiting patiently since 1997 for the next franchise tackle to be drafted.
On Thursday, Auburn's Greg Robinson could bring back the echoes of the five cornerstones Willie Roaf, Tony Boselli, Jonathan Ogden, Orlando Pace and Walter Jones who arrived in the mid-1990s to revolutionize the tackle position.
"He's so heavy-handed and so athletic, I think he's going to be the next Orlando Pace," said an executive in personnel for an AFC team. "He's got a chance to be a Hall of Famer some day."
In a Journal Sentinel poll asking 20 personnel people to name the best player in the draft, defensive end Jadeveon Clowney easily carried the day, but Robinson did tie for second place with two votes.
Texas A&M's Jake Matthews, the other leading man in a draft chock full of tackles, also received a vote.
"I do," Atlanta Falcons general manager Thomas Dimitroff replied to the idea that one or more of the tackles could become one of those "dancing bears" of the past. "The top end for tackles is very good this year.
"Greg is a massive man with top-notch athleticism for the position. He's got a lot of natural ability with the arrow definitely pointing up."
Roaf (11 Pro Bowls) already has been inducted into Canton. Ogden (11), Pace (seven) and Jones (nine) probably will some day, and Boselli (five) was headed there, too, before injury cut short his career after seven seasons.
The last Pro Bowl appearance by the big five was Jones' in 2008. Since then, Cleveland's Joe Thomas (seven seasons, seven Pro Bowls), the No. 3 selection in 2007, has been the most consistent and probably the NFL's finest tackle, but he seldom dominates like his predecessors did.
As Robinson (6 feet 5 inches, 329 pounds, 4.91-second time in the 40-yard dash) prepares to be a single-digit selection, it's instructive to look back at how the greats entered the league.
Roaf (6-4½, 307, 5.01), the No. 8 pick by New Orleans in 1993, started four years at weak-side tackle for Louisiana Tech and was overpowering.
"I don't see any negative right now," said the late John Butler, then GM of the Buffalo Bills. "He has almost natural pass pro ability."
Boselli (6-7, 323, 5.12), another four-year starter, was rated Southern California's best tackle since Hall of Famer Anthony Munoz, who ran 4.9 at 285 coming out in 1980. Boselli went No. 2 to Jacksonville in 1995.
"Mike Kenn's a better pass blocker but not as physical as this guy," Miami scouting director Tom Braatz said. "He's great."
Ogden (6-8, 318, 5.05) went No. 4 to Baltimore after starting for 3½ years at UCLA.
"Has all the tools in the world but, unless he becomes a more physical and aggressive player, he will never become as great as he can become," the late Joel Buchsbaum wrote in his 1996 Pro Football Weekly draft guide. "Is a better athlete than Tony Boselli, (John) Hannah and (Mike) Munchak were. Has unlimited, Anthony Munoz-type potential."
In 1997, the debate for No. 1 tackle raged between Pace (6-7, 328, 4.97), a third-year junior from Ohio State, and Jones (6-5, 303, 4.70), another underclassman who played merely one season at Florida State.
Of Pace, who went No. 1 to St. Louis, Saints GM Bill Kuharich said, "He just toyed with people. The amazing thing was, in all the games I saw he was on the ground maybe once or twice. He'll play well forever."
Of Jones, who went No. 6 to Seattle, New England scouting director Charley Armey said, "He's the best player in this draft. Two years from now he'll be an all-pro for 12 straight years. He's better than Pace. More athletic, and quicker."
Make an evaluation. Exercise a pick. Get one end of the line shut down for a decade.
Players of that ilk made personnel work seem so simple.
Since then, disappointing tackles drafted high in the first round litter the landscape. As the college game moved away from pro sets to spread formations, it became more difficult for scouts to identify NFL-caliber ability.
The frustration level reached its peak five years ago when tackles Jason Smith went No. 2, Andre Smith went No. 6 and Eugene Monroe went No. 8.
Jason Smith is out of football, Andre Smith has been an average right tackle in Cincinnati, and Monroe was traded from Jacksonville to Baltimore last fall for a pair of mid-round draft choices.
No one doubts Robinson's prowess as a run blocker. He drives defenders off the ball.
Of course, Robinson had a ton of practice doing it at Auburn, where the Tigers rushed 63% of the time in 2012 and 71.9% in '13.
Depending on which team selects Robinson, he probably can expect just the opposite ratio next season given the proliferation of passing in the NFL. And, as one would expect from a third-year sophomore from Auburn, pass blocking is the weakest part of his game.
"He's really fundamentally (sound) with his feet but we have not got his hands where I want them yet," said J.B. Grimes, Robinson's line coach in 2013. "And if there is one thing we have got to fix if I had a chance to do that it would definitely be his hands, especially in pass protection."
Largely because of the uncertainty regarding Robinson's pass blocking and the widespread certainty about Matthews' overall game, Robinson had just a slight edge over Matthews in a Journal Sentinel poll asking 18 national-type scouts to rate their five best offensive linemen regardless of position.
A first-place vote was worth five points, a second-place was worth four and so forth.
Here were the first-place votes: Robinson, 11; Matthews, 6; and Zack Martin, one.
Here were the point totals: Robinson, 80; Matthews, 76; Taylor Lewan, 48; Martin, 43; Cyrus Kouandjio, 11; Xavier Su'a-Filo, seven; Joel Bitonio, three; and Ja'Wuan James and Spencer Long, one.
"Matthews isn't Jonathan Ogden in dimension, but he's got the genealogy and the durability," said Phil Savage, who helped draft Ogden as the Ravens' director of college scouting. "He may not end up being as spectacular as Greg Robinson, but Day 1 he's closer to being ready to play."
The offensive line connoisseurs would settle for greatness from even one of them.
John Urschel, G, Penn State: Last month, he won the Sullivan Award as the country's top amateur athlete. Scored 43 on the Wonderlic. Taught math classes at Penn State last year. Two-year starter at right guard might have a better chance at center. On the small side (6-3, 312) but loves the game and wants to play badly before pursuing his promising academic future.
Chris Watt, G, Notre Dame: Three-year starter at left guard. Typical blue-collar grinder. Played strong, smart and aware. Then, at the combine, he measured at just 6-2½ and ran a slow 5.5 40.
Syd Kitson, G, Wake Forest: Third-round pick in 1980. Undersized but a top-notch athlete. Injuries ruined his first three seasons, but he started nine games at guard in 1983 and entered '84 as a starter. New coach Forrest Gregg, however, preferred more robust blockers, so Kitson was waived after seven games to make way for guard-tackle Keith Uecker.
NFL personnel man: "Everybody jokes about the Big Ten now. But when I look at offensive linemen that's the first place I look because they still play football in the Big Ten. It's still the Hayes-Schembechler mentality to a degree. Some of those other teams have changed things around. But you take Ohio State, Michigan, Wisconsin, Kirk Ferentz at Iowa. They still take pride. They don't run around you. They try to go right through you."
-05-03-2014 #2
Re: Bob McGinn Draft Series: Offensive LinemenLargely because of the uncertainty regarding Robinson's pass blocking and the widespread certainty about Matthews' overall game, Robinson had just a slight edge over Matthews in a Journal Sentinel poll asking 18 national-type scouts to rate their five best offensive linemen regardless of position.
A first-place vote was worth five points, a second-place was worth four and so forth.
Here were the first-place votes: Robinson, 11; Matthews, 6; and Zack Martin, one.
Here were the point totals: Robinson, 80; Matthews, 76; Taylor Lewan, 48; Martin, 43; Cyrus Kouandjio, 11; Xavier Su'a-Filo, seven; Joel Bitonio, three; and Ja'Wuan James and Spencer Long, one.
One, likely due to his athleticism and upside, Robinson takes the top spot. But the point total difference between he and Matthews is negligible; out of 270 total points represented there, Robinson has 29.6% and Matthews has 28.1%. That's pretty darn close, and seems to support what Nick Wagoner said in his recent chat about a choice between the top two tackles being one in which you're splitting hairs.
The second thing worth noting, and which kind of aligns with my personal viewpoint, is the dropoff from Robinson/Matthews to Lewan (who had 17.8% of total points). Lewan is a fine prospect and would make a nice consolation prize if the Rams can't get Robinson or Matthews. But there's been recent talk, mostly from Kiper, about Lewan being ranked over Matthews, and I just find that rubbish, and it seems these scouts would agree.
-05-03-2014 #3
Re: Bob McGinn Draft Series: Offensive Linemen
The one knock I've heard on Matthews is arm length. At OT you need to be longer armed than inside. Despite that, I wouldn't object to Matthews for his pass protection skills. I feel confident that Boudreau can raise his skill level for run blocking too. It's all good.
Go Rams!
-05-03-2014 #4
Re: Bob McGinn Draft Series: Offensive Linemen
Greg Robinson may or may not live up to his athletic potential. He is without doubt, the most physically gifted O-lineman in the 2014 draft. That said, I cant help but feel extremely nervous about drafting him, given that we have (IMO) a better option.
Jake Matthews from the time he was a young boy has had continual access to an NFL Hall of Fame O-lineman dad, who was capable of playing every single position on the O-line. We are talking hundreds - more likely thousands of hours of father to son tutelage. Jake's NFL bloodlines are perhaps unsurpassed in NFL history. Talk about a great gene pool, if there is a plugin and play guy in this draft, it is Jake Matthews. Should injuries shake up our O-line personnel again this year, Jake M. could play any position on the line. If Jake Long is slow coming back or gets hurt again, and Saffold were not available, who would you rather have at left tackle, Jake Matthews or Greg Robinson, particularly with Sammy B. coming back from knee surgery?
Maybe Paul Boudreau thinks he can round Greg into shape within a year, who knows? Even so, Id still give the nod to Matthews. Jake brings techniques/knowledge/intangibles right now that Robinson can only hope to bring several years down the road.
Think Peyton Manning for a moment; would he have had the early success he did without the tutelage of his dad? My guess is no. Great genes, NFL bloodlines along with years of NFL experience at your immediate disposal on a daily basis cant be discounted. Peytons football smarts started way way back. He had a tremendous head start, and hed likely say so if asked. Players coming out of college possessing these attributes are few and far between - perhaps once every decade.
Countless times I have read on this site how this or that member is sick and tired of excuses - we need to win now! If so, would you want to draft yet another project? Is there anyone here that thinks Greg Robinson is more NFL ready than Jake Matthews? I certainly dont.
It will be very interesting to see how our draft pans out. I am just a fan, and as such have no reliable info on how Les, Fish, and Boudreau view our O-line at present. It is possible that Gregs awesome physical attributes are such that we would consider taking him and letting him start at left guard, with the fervent hope J.L. and Saffold stay healthy. I am hoping we take big Jake and solidify a position on our line for the next 10 or 12 years. My two cents ..
-05-03-2014 #5
Re: Bob McGinn Draft Series: Offensive Linemen
-05-03-2014 #6
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Re: Bob McGinn Draft Series: Offensive Linemen
Still don't like the idea of getting an OL with the #2 pick when we can get one of Clowney, Mack or Watkins. Think the earliest we should look at OL is #13 or even the 2nd round.
What if you could get Watkins, Donald and then OL Bitano with your first 3 picks ? Would that satisfy everyone's need for an OL if we eneded up with those 2 studs up front. We still lack DBs if we do that which is why I want a trade down.
-05-04-2014 #8
Re: Bob McGinn Draft Series: Offensive Linemen
Upgrades the line highly, makes our front four scary good, solidifies the back end, and give us a big target WR.
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text: This Has Got To Be The Weirdest Video To Come Out Of Valve's Source FilmmakerTina Amini7/09/12 10:00pmFiled to: Source filmmakerwatch thisWatch ThisPlay ThisValveTeam Fortress 262EditInvite manuallyPromoteDismissUndismissBlock for kotakuHideShare to KinjaGo to permalink Dammit, Steven, will you just answer the question?! Oh, and, for your reference. Braeheavs Books [YouTube via Reddit]Reply62 repliesLeave a reply


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Join us on our new podcast each weekday for an interesting story, well told, from Charisma News. Listen at charismapodcastnetwork.com.
"The Lord said to him, 'Who gave man his mouth? Who makes him deaf or mute? Who gives him sight or makes him blind? Is it not I, the Lord? Now go; I will help you speak and will teach you what to say'" (Ex. 4:11-12).
In Old Testament times there were usually only a few prophets on the whole earth at any one time. Sometimes prophets were contemporaries (Haggai and Zechariah, Isaiah and Jeremiah), but for the most part they operated in isolation as the lone mouthpiece of God.
They often were not incorporated into the daily religious life and traditions but stood apart, separated unto God.
No prophet exemplified this more than Elijah, who stood alone against King Ahab, the prophets of Baal, and the sins of a rebellious people. John the Baptist fits that mold as well—the man of God coming out of the wilderness to proclaim repentance because the Day of the Lord was imminent.
These prophets spoke with a clear and unmistakable, "Thus saith the Lord!" The authority of God's prophets was not limited to the general content or the main ideas of their message. Rather, they claimed repeatedly that their very words were the words that God had given them to deliver.
There was never a question about accurately discerning the genuine word from God. For the prophet, it was only a matter of whether he had the courage to deliver it.
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Motor City
Adrien Brody Latest Actor to Move to 'Motor City'
- By Kate Erbland
- @katerbland
- August 24, 2012
Let's take this moment to recount the many actors who have been attached to star in Albert Hughes' Motor City. First, Dominic Cooper was set as the lead, then he left and Jake Gyllenhaal looked poised to step in, and then ol' Gylley left and Gerard Butler swooped in for...
Gerard Butler to Take the Wheel in Albert Hughes's 'Motor City'?
- By Kate Erbland
- @katerbland
- March 29, 2012
Albert Hughes's next film (sorry, Akira remake that I pray to God never happens), Motor City, has been spinning its wheels for months now, mainly because it's been unable to hold on to a leading man. The film has had a number of hot names attached to it for its...
Jake Gyllenhaal Revs Up Negotiations With Albert Hughes For 'Motor City'
- By Nathan Adams
- @templeofreviews
- March 7, 2012
Albert Hughes' next project, Motor City, is in a bit of a pickle. You see, Dominic Cooper was all set to star in the movie, playing a recently released prisoner going about the business of tracking down the men who framed him and thus sent him away. There have been...
Amber Heard to Star Opposite Dominic Cooper in Sexiest Revenge Thriller Ever, 'Motor City'
- By Kate Erbland
- @katerbland
- November 21, 2011
Despite the fact that her latest television turn went bunny tail up with the cancellation of The Playboy Club, actress Amber Heard isn't letting that slow her down, as she's just signed on for next starring feature role. Heard will play the female lead in Albert Hughes' Motor City from...


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Shooting Rainbow Photos with Diana F+6 11 Share Tweet
Want even more colorful photos? Grab a pair of scissors, some sticky tape, colorful cellophane, and of course your camera, and let's get crafting!
I fancy rainbows so much that I decided to mix that with my photos.
What you'll need:
- A pair of scissors
- Sticky tape
- Cellophane in different colors
- Your camera
STEP 1: Cut strips of cellophane…or cut out any shape, I guess.
STEP 2: Use sticky tape to stick those strips in your camera's Mask Mount, the area directly behind the lens.
STEP 3: Load a fresh roll of film and capture the world.
I did this experiment with my Diana F+ and the result was awesome!!!
You can also use just one colour or two or three. It's up to you.
The Diana F+ is a new twist on the '60s classic cult camera. Famous for its dreamy and soft-focused images, the Diana F+ is now packed with extra features such as panorama and pinhole capabilities. Available in our Online Shop.
written by sunbaby on 2012-07-06 in #gear #tipster #colorful #art #tipster #diana-f #mask-mount #rainbow #lomography #cellophane #tips


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March 18th, 2013 by claremont
Come and see us at the Amex Stadium Wedding Fair on Sunday 24th March. … Read the rest
October 15th, 2012 by claremont
A big hello to everyone we met at the Wedding Fair this Sunday.
Hopefully we will see … Read the rest
October 6th, 2012 by claremont
We are a wedding venue Brighton can be proud of and we'll be at the … Read the rest
August 26th, 2012 by claremont
To Lucy and Matt who got married here on Saturday. Despite the forecast the weather … Read the rest