text:
|Publication number
|Publication type
|Application number
|Publication date
|Nov 18, 1997
|Filing date
|Jun 28, 1996
|Priority date
|Nov 19, 1993
|Fee status
|Publication number
|Kung-Pu Li
|Original Assignee
|Itt Corporation
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|Patent Citations (4), Non-Patent Citations (32), Referenced by (84), Classifications (7), Legal Events (4)
|External Links: USPTO, USPTO Assignment, Espacenet
This is a continuation of application Ser. No. 08/154,601, filed on Nov. 19, 1993 now abandoned, entitled AUTOMATIC LANGUAGE IDENTIFICATION/VERIFICATION SYSTEM.
This invention relates to language identification and verification systems in general, and more particularly to such a system where language decisions are made based on a comparison of well-matched reference speakers in each language for which identification is to be made.
A language identification/verification system operates on unknown speech to identify the language being spoken, or to verify that the spoken language corresponds to a predetermined language. Such systems find application in both the intelligence and commercial environments, as, for example, in conjunction with machine translation systems for converting speech from one language to another. Moreover, due to the substantial, and increasing, demand made on computational resources by speech identification systems, it will be readily understood that a removal of one of the variables, such as language, can be very desirable. Thus, automatic language identification may also find important application as a part of the "front-end" processing for a speed recognition system. Then the language identification system must operate without any antecedent knowledge of the language for the speech to be identified.
A number of language identification/verification systems are found in the prior art. In 1977, House et al. suggested a statistical model for language identification, with several different approaches to implement an automatic identification system. (House, A. S., and Neuberg, E. P., "Toward Automatic Identification Of Language Of An Utterance. I. Preliminary Methodological Considerations", Journal of the Acoustical Society of America Vol. 62, No. 3, pp. 708-713, 1977). Essentially contemporaneously, Li and Edward reported on several experiments involving automatic segmentation of a speech utterance into six major phonetic segments followed by extraction of a segment occurrence using a statistically model. Such sequential segmental information was used to identify the language spoken. (Li, K. P., and Edward, T. J., "Statistical Models For Automatic Language Identification", ICASSP-80, pp. 884-887, 1980). A few years earlier, Doddington, et al. reported using selected fixed length spectral parameters to form language reference patterns, in identifying the spoken language by searching the frequency of such patterns. (Leonard, G. and Doddington, G. R., "Automatic Classification Of Languages", RADC Final Report, RADC-TR-75-264, 1975). Roughly, a decade later, Goodman et al. described an extraction of speech formants, pitch values, and other short term spectral features, and using them in a statistical approach to identify the spoken language. (Goodman, F. J., Martin, A. F., and Wohlford, R. E., "Improved Automatic Language Identification In Noisy Speech", ICASSP-89, pp. 528-532, 1989). In 1991, Sugiyama described an experimental study that used spectral parameters in short time frames to measure the closeness between references and unknown input to identify the language. (Sugiyama, M., "Automatic Language Recognition Using Acoustic Features", ICASSP-91, pp. 813-816, 1991). Approximately a year later, Muthusamy et al. described the use of an artificial intelligence technique to segment speech into gross phonetic classes to form a statistical model for identifying a language. (Muthusamy, Y. K. and Cole, R. A., "Automatic Segmentation And Identification Of Ten Languages Of Telephone Speech", Proceedings of ICSLP, pp. 1007-1010, 1992). Earlier this year, Zissman described the use of a statistical model, specifically a Hidden Markov Model, or HMM, to represent a language model and to process speech spectral statistics at the frame rate for identifying language. (Zissman, M. A., "Automatic Language Identification Using Gaussian Mixture And Hidden Markov Models", ICASSP-93, RAA.8, Minneapolis, Minn., April, 1993). As will be known to those skilled in the art of the invention, all of these efforts at language identification have shown only moderate success.
Unlike many speech identification systems, a language recognition system must operate from the premise that the speaker is unknown, and that the text to be evaluated is unconstrained. With this premise, automatic language identification becomes a challenging problem. In addition to the non-ideal operating environment, variations due to duration of speech, channel characteristics, and background noise make processing even more difficult. A major obstacle to the realization of an acceptable level of accuracy from prior-art language identifiers results from the wide variation in speaker characteristics found in those spectral features most often used by such prior-art language recognition systems. All of the prior-art systems described above are based on the use of pooled speech samples for multiple speakers, cataloged by language, to form a speaker-independent model for that language. Moreover, as will be known, all prior-art speech recognition, speaker identification, and language identification systems operate generally within the same set of parameters: namely, short term spectral representation.
Due to large variations between speakers at the short term spectral level, performance of the language recognition system is likely to be influenced by individual speaker characteristics. Thus, a general model for a language covers only the common physical features among all of the speakers in the training data. This will result in a large overlap of features and spectral characteristics among the different languages. A recent study shows that speaker differences within a language are much greater than the differences between two different languages for a single bilingual speaker. (Abe, M., Shikano, K., and Kuwabara, H., "Statistical Analysis of Bilingual Speaker's Speech For Cross-Language Voice Conversion", JASA, Vol. 90, No. 1, pp. 76-82, 1991). Therefore, confusion between language will be very large, and the likelihood of error in a language recognition system will be substantial if the input features for a language recognition system are limited to the acoustic phonetic features.
Another limitation of prior an systems is that such systems have generally used either short term spectral features at a 10-20 msec frame rate, or an automatic speech recognition technique to segment a speech sample into discrete units, such as phonemic or gross phonetic feature classes. As will be known, the phonetic technique does not bear any linguistic structure information, which information contains most of the significant distinctions between major languages--such as syllabic, word's, and grammatic structures. Similarly, with current technology, segmentation of speech in speech recognition systems does not provide an identification of speech segments with an acceptable level of accuracy. The classification errors may propagate into the statistical modeling and thereby degrade the matching processes.
Accordingly, it is an object of this invention to provide a language identification/verification system which minimizes error due to differences in speakers within a language. A further object of the invention is a language identification/verification system which detects vocalic or syllabic nuclei, and then extracts related phonetic features to represent the syllabic structure at the vocalic centers or syllabic nuclei. Among the applications of such an automatic language identification/verification system are the following:
(1) such a system can detect the language of incoming speech and direct such speech to an appropriate receiver trained in the target language--e.g., a telephone caller could be automatically connected to an operator fluent in the language of the caller without having to deal with an interface in a language foreign to the caller;
(2) such a system would find ready application as a "front end" for an automatic speech recognition system such as an automatic transcriber or translator, which systems are often designed to be language-specific.
(3) such a language identification system will also be useful to a decision as to which phonetic features a speech recognition system might need as its input--e.g., Chinese, being a tonal language, requires the fundamental frequency (pitch) as a basic and necessary phonemic feature for speech recognition, whereas English does not have such a requirement.
A Language Identification/Verification System is disclosed comprising a means for processing spoken text into frames of speech and a means for detecting and extracting speech features from the frames of speech, which in combination operate to identify phonetic speech elements, matching means for comparing the phonetic speech features with stored referenced phonetic speech features and establishing a match score for the comparison proportional to a degree of similarity between the phonetic speech features and the stored reference phonetic speech features, and decision means for identifying input speech to the system as corresponding to one of a plurality of languages, whereby the language identification for the input speech is established on the basis of a comparison of the match score with at least one predetermined threshold score associated with one of the plurality of languages.
FIG. 1 is a diagram of the major components of the system of the invention.
FIG. 2 depicts operation of syllabic nuclei marking by an artificial neural network.
FIG. 3 represents diagrammatically the method whereby the artificial neural network of FIG. 2 is trained.
FIG. 4 depicts operation of syllabic feature encoding according to the invention.
FIG. 5 shows the flow diagram for a two level artificial neural network for language identification, including (a) the syllabic level neural network, and (b) the second level neural network with multiple syllabic structure.
FIG. 6 shows the Hidden Markov Model for syllabic extraction and language matching according to the invention, including (a) the syllabic modeling at each syllabic nuclei, and (b) the matching of an HMM to test the utterance to obtain matching probability for a language.
FIG. 7 depicts the matching process and the language decision process according to the invention.
The overall structure enabling operation of the invention is shown in the diagram of FIG. 1. In that figure, the first element, Front-end Processing/Parameterization 1, operates on the input speech to reduce variations in speech signals due to environmental factors--e.g., differences in channels, microphone and amplitude settings. Such preprocessing/parameterization functions are known to those skilled in the art of the invention, and any number of prior-art embodiments of such functions may be applied to this element of the invention. The remaining functional elements, which are the core functions of the invention, will be described in detail in following sections. Briefly, however, the elements Syllabic Nuclei Marking by ANN 2 and Syllabic Feature Encoding 3 operate to extract language-specific features at a syllabic level from the Front-end Processing/Parameterization output. The Message Matching 4 element operates in relation to Language Reference 5 to minimize differences among speakers. The Decision Making 7 element operates on information developed by the preceding elements to make a determination of the language of the input speech. It is also noted that the invention can be implemented through the use of three different functions for language identification, which functions can be used independently or in conjunction with each other. The first such function is the Nearest Neighbor analysis model, which finds the best speaker within a language in order to decide what language is being used. The second function is an Artificial Neural Network analysis model, or ANN. The third function is a syllabic-based Hidden Markov Model or HMM, which is a speaker-pooled or a speaker-independent approach to represent a language. Although each of these language identification functions will be characterized by particular advantages, all three are competitive in performance and accuracy.
Hereafter, the core functions of the invention are described in detail.
In any language identification application, it must be assumed that the reference and testing utterances represent different speakers, different channels and different environments. The front-end processing operates to reduce speech variations resulting from such differences and/or to achieve a workable normalization of such input variations. Initially, input speech is sampled and converted to parameters usable by the processing steps of such a system. In a preferred embodiment of the invention, such parameterization is established through operation on the input signals by fourteen bandpass filters covering the frequency range from 300 hz to 3300 hz, the output of such bandpass filters being sampled every 20 msc. and converted to Olano Parameters--i.e., rms normalized fourth root of the amplitude within each band, such as was described in Boll, S., Porter, J. and Bahlet, L., "Robust Syntax Free Speech Recognition", ICASSP, pp. 179-182, April, 1988.
To normalize, and therefore reduce the effect of variation in input signals, due to text and channel differences among the reference and testing utterances, there are a variety of normalization processes that may be applied to the parameterization outputs. Two such normalization processes commonly utilized are: blind deconvolution and z-score normalization. As will be known, the blind deconvolution process is described by the equation: ##EQU1## Likewise, z-normalization, which is a process of mean removal and variance normalization is described by the equation: ##EQU2## These normalization and parameterization processes are well known to those skilled in art of speech identification systems and will not be further discussed here.
As previously discussed, prior art language identification systems have commonly used short term spectrum as the basic feature space, with generally unsatisfactory results. This invention is directed to the extraction of language features at the segmental level. To avoid the language dependent phonetic segmentation process, with its obvious limitation for a language recognition system, a process has been developed to mark the anchor points of syllable nuclei, and thereby extract the spectral features for the syllabic structure without any reference to phonetic events. The essential process of this aspect of the invention is, first, to develop a learning process for detecting and marking those anchor points corresponding to syllabic nuclei, or vocalic center peaks, and second, to utilize those markers for extracting and encoding phonetic sequential events near the syllabic nuclei. A sample size is chosen to correspond to the number of phonetic events found, and those sample contents represent the phonetic spectral structure near the syllabic nuclei.
FIG. 2 depicts, in organizational form, an automatic marking function for detecting and marking the vocalic centers and syllabic nuclei for all languages. Implementation of this function is essentially based on the operation of a trained Back Error Propagation Multi-Layer Perceptron (BEP-MLP) neural network. Training of this network, is accomplished with a multiple language database using hand-marked syllabic nuclei as the teaching data. In an experimental embodiment, 30 seconds of speech for each of 5 different languages was used.
The training of the BEP-MLP artificial neural network is depicted in FIG. 3, and includes the following steps:
i. The speech data is marked to detect the syllabic nuclei of the sample multi-language speech data--30 seconds of speech data for each of five languages in an experimental embodiment. Such marking may be entirely by hand, or by using a known methodology for automatically detecting such syllabic nuclei, followed by a manual review of the results from such an automated method to correct erroneous markings from that automatic method.
ii. A BEP-MLP neural network is trained on the marked syllabic nuclei for the sample speech data. In a realized embodiment of the invention, inputs to the neural network were five frames of amplitude, their time derivatives, left and right loop areas, and the five lowest frequency outputs. Using the described sample, a total of forty-five values would be input to the neural network. In the described embodiment, the teaching function for the network consisted of a "1" for the target segment and a "0" for the non-target segment. The network uses only one hidden level, with one output to indicate "marking". Simple decision logic is implemented to separate the neural network output in to frame-by-frame markings of syllabic nuclei detection.
iii. After the training process, the neural network is employed to relabel the marked speech samples as a check for the learning efficiency of the network. In the described embodiment, the inconsistency between hand-corrected markings and that of the trained neural network was less than 3%, a result which is viewed as being essentially equal to the inherent error in the hand-marking process.
iv. The procedure of labeling, correction, training, and re-labeling is then repeated on larger and larger speech samples until a fully-trained neural network is realized. This network is then used without further modification to label and mark other databases of reference speech.
From the results achieved in the described embodiment of the BEP-MLP neural network, the following conclusions are drawn:
(a) The neural network outputs are consistently, and closely matched to the hand-marked data.
(b) In the training of the network, manual markings are needed only for correction, which significantly increases marking speed.
(c) Marking of unfamiliar languages can easily be accomplished.
(d) The neural network markings can be implemented as an on-the-fly, front-end process to automatically locate syllabic nuclei without significant delay.
In summary, input parameters to such a BEP-MLP neural network cover multiple frames of speech amplitudes and time derivatives, along with filter outputs and vocalic-center related features. Such a neural network has a decision process to provide a binary decision for each individual frame of speech data. Thus, if a syllabic nucleus is detected, the output of the network is binary "1"; otherwise the output will be a "0".
Syllabic Feature Encoding, 3 of FIG. 1, is illustrated in greater detail in FIG. 4, which shows the flow diagram of encoding for a fixed number of speech frames prior to the syllabic nuclei marking (backwards in time). As will be seen in that figure, feature extraction, which forms the basis for the subsequent feature matching step, is done by encoding a number of frames in sequence near the marks made during the marking process described above.
This element of the invention extracts the acoustic phonetic features to represent the syllabic characteristics of a language. The detected syllabic nuclei are used as anchor points, and the process extracts the phonetic events surrounding each such syllabic nucleus.
In a realized embodiment of the invention, the number of frames needed to encode syllabic features is in a range from four to six. There are at least two well-known encoding techniques which may be used for encoding of the syllabic features: (1) variable frame encoding and (2) arc-length encoding. Both such encoding techniques have been found to work with the invention, and others will be apparent to those skilled in the art.
With variable frame encoding, a determination that the distance to a frame under consideration from an adjacent frame does not exceed a specific threshold distance causes the frame to be discarded, and the next adjacent frame to thus be considered. The process continues until a specified number of frames have been extracted. For arc-length encoding, the arc-length is accumulated from frame to frame. When a length is achieved which is larger than a predetermined threshold length, the frame under consideration at that time is encoded. These two encoding techniques depend on acoustic changes in time, and are minimally effected by the speaking rate. Frames so encoded form a single feature vector representing the sequential phonetic event at the on-set of a syllabic nucleus.
As will be understood by those skilled in the art of the invention, the syllabic on-set is a spectral representation of the sequential events in phonetic changes before a syllabic nucleus. The essential advantage of this methodology is a reduction in feature variation due to different speaking rates in the input speech. The methodology additionally incorporates a selection procedure to ensure that the frames selected for encoding are not chosen predominantly from "silent" frames, such as would occur in a short syllable--e.g., "the" and "a"--at the beginning of a sentence.
The next step in the operation of the language identification system of the invention, the feature matching process, 4 of FIG. 1, will, in a preferred embodiment be implemented using a Nearest-Neighbor determination as described in the next section. However, alternate embodiments of the invention may incorporate (1) a multi-level artificial neural network using back-error propagation or (2) a Hidden Markov Model, operating at the syllabic structure, for performing some or all of the feature matching functions. Such alternative embodiments will also be described in following sections.
As explained above, the base-line system for the feature matching process of the invention uses the Nearest-Neighbor process for determining a match between input speech features and reference speech features. This process, which represents a non-parametric approach for speaker identification and uses the average Nearest-Neighbor distance between speech features is described in a pending patent application, Ser. No. 07/918,560, entitled SPEAKER VERIFIER USING NEAREST-NEIGHBOR DISTANCE MEASURE, filed by A. Higgins and assigned to FIT Corporation, the same assignee as the for the present application. A major advantage for the Nearest-Neighbor algorithm described in the referenced application is that training samples from each speaker can be limited, since there is no statistical estimation; all samples form their own local distribution without any estimation. The difference measure becomes a matching of distributions between a reference and an unknown. With subsequent normalization of environments--which includes variations of length, content and speaker biases in those measures, the performance of matching a target speaker becomes excellent.
An essential difference in the methodology used here and that of the referenced application, however, is found in the input data to the matching process. Instead of evaluating speech parameters at a frame rate, as is the case in the referenced application, the input sample used by this invention is obtained through the syllabic encoding of multiple frames. Thus, the matching process is accomplished by finding the average score of the nearest-neighbor distance for whole utterances for each reference speaker. Another significant difference in the process of the invention from that of the referenced patent application is that the system of the invention also groups together all speakers who speak the same language. Additionally, as described more fully below, the system of the invention includes an additional scoring step for identifying the language spoken.
In an alternative embodiment, a two-level artificial neural network may be used to replace the nearest neighbor technique in the feature matching process. Such a two-level artificial network is illustrated in FIG. 5. As can be seen from the figure, the two-level artificial network involves two stages of training. The first level BEP-MLP neural network is trained to discriminate one language from the remaining languages at the single syllable level. Therefore, one BEP-MLP neural network will be used for each language to be tested. At a second level, another BEP-MLP neural network combines all of the outputs from the first level BEP-MLP neural networks, and accumulates multiple syllables. The second level, BEP-MLP neural network then further separates languages by their sequential patterns. In this embodiment, each first level neural network can learn to separate a target language when multiple speaker data are pooled together. As will thus be understood, such a neural network can learn to separate all target languages when multiple speakers' data are pooled together.
In another embodiment, an HMM may be used as an alternative to both the syllabic extraction and the matching processes of the invention by establishing separate such models to represent each individual language to be evaluated. Operation of such an HMM is depicted in FIG. 6. In this embodiment, the HMM is trained as an underlying statistical model of a language's syllabic structure. The model is forced to use syllabic markings as the anchor point of the fixed state of the model to learn the statistical characteristics of variable duration spectral strings related to the anchor point.
The basic concept of this process is in the use of a finite state Markov chain as a statistical model to extract the probability of the spectral pattern, and to match language characteristics. The process not only observes each syllable, but also uses the Viterbi tracking technique--as described in Forney, G. D., "Viterbi Algorithm", Proc. of IEEE, Vol 61 (3) March 1973, pp. 268-278, to string together a multiple syllable sequence into the best possible form for describing the testing utterances with the language structure trained in the HMM. Therefore, the overall encoding score for matching the testing utterance toward the language model is used for language identification. This process will eliminate use of a fixed number of frames in the syllabic feature extraction, as described above in the discussion of syllabic feature extractions, and instead covers a fixed time span. This HMM embodiment will however require a very large set of speech samples in order to train the HMM model to be speaker independent for the language.
To effectively use the spectral features in a speech identification system, it is necessary to quantify the operating environment. For speaker identification, the target speaker should be included in the reference set, and, accordingly, multiple recording sessions for each speaker are required. For language identification, on the other hand, the speaker of the test speech would normally not be included among the reference speakers.
As previously described, it has been established that speaker differences between a pair of speakers are much greater than language differences obtained from a single bilingual speaker. From this, it follows that there exists a similarity between speaker identification and language identification, and that the two closest speakers identified by a speaker identification system will have similar speaking characteristics and/or a similar language structure. Thus, reducing the differences between two speakers to find the remaining language differences becomes an essential process in dealing with such speaker variations.
If the two closest speakers are speaking the same language, the differences will be smaller than if they are speaking different languages. While speaker and language difference are difficult to separate, they can be distinguished with proper decomposition. As is well known, a speaker identification system can find matched utterances for the same speaker. Thus, language identification can be determined by finding the best matching speaker for a known language.
FIG. 7 depicts a speaker identification system according to the invention which operates so as to use these principles to advantage. As can be seen in that figure, all speaker models from the same language are grouped together. After an appropriate normalization of the message distances for comparable scores, each such language group will provide a small set of best-speakers against which an unknown utterance can be compared. From this, a score corresponding to the comparison as to each language is obtained. A minimum score is defined as the minimum message difference measure between the test sample and all reference speakers in each language as determined in such a comparison. An average score is defined as the average of all message difference scores between the test utterance and all speakers in a language. Both minimum and average scores in each language may be used in the decision process of the invention for identifying the language of the tested utterance.
In the operation of the invention, the matching process estimates the average minimum distance (or distortion) from the test sample to the reference samples, or vice versa. In an ideal case, one would only extract language differences for language identification and, similarly, only extract speaker differences for speaker identification. Realistically, however, these two differences (i.e., language and speaker) cannot be completely separated in the front-end processing of a language identification system, especially given that the input feature set inherently consists of both speaker and language characteristics. Therefore, speaker variation in language identification system must be addressed in the decision process.
To achieve perfect speaker identification without any language features, language identification in such a system would approach random chance. Similarly, a perfect language identification system cannot distinguish speakers within the same language or cross over to different languages. Thus, any speaker of a language may be the reference speaker for that language. In order to obtain the best (i.e., nearest neighbor) matching as a message difference measure, a perfect language identification system must be completely independent of speaker variations within a language. Every match and measure from the test utterance to the different speaker references within a target language must always be the best (i.e., minimum) compared to any speakers from different languages. Therefore, the average score for any group of speakers should also perform well under such conditions. The differences between minimum scores and average scores for language identification can also indicate the degree of change for language distinction among speaker differences. It will of course be recognized that under realistic conditions, the operating environment for a language identification system will be located between those two extremes. Thus, there will always be some speaker and language differences in any set of features.
The decision process of the invention essentially comprises an evaluation of scores from the matching process against predetermined threshold levels. As indicated above, a best, or minimum, score is established for a matched speaker for each language group. Similarly, the average score for a language represents an average of speaker matching distances within that language. It should be understood that, if the database for the invention includes n languages, then n minimum scores and n average scores will be usable, either separately or in combination, for language identification or verification.
The basic decisional process of the invention is to use the scores from the matching process as the difference between two messages, either from the same or different languages. If the two messages are in the same language, the score will be smaller than if the messages are from two different languages.
In the ideal circumstance of the input speech features being completely (or at least essentially) free from speaker differences, the average score would be expected to provide the best value for making a language decision. In the more usual case of the input features containing both speaker and language characteristics, comparison with the minimum score will produce more efficacious result, due to use of the best-matched speaker in each language as the threshold score. For example, if speech is recorded with high quality recording equipment and with readings made by only same-gender speakers, the minimum score will be expected to outperform the average score. On the other hand, if the speech is recorded from telephone lines (i.e., representing narrow bandwidth and line noise) and the speech is spontaneous monologue from both males and females, minimum scores will be expected to perform worse than average scores. In such a non-ideal environment, an average of a small portion (i.e., one-fourth to one-third) of best scores with average scores within each language will usually provide the best performance.
As will be appreciated, the system of the invention is flexible in its scoring methodology and the learning process can therefore be based on different databases to obtain optimum results by testing both types of scoring or combined scores.
It will thus be seen that the invention overcomes the problem of short-term acoustical spectrum lacking language structure information, by detecting vocalic or syllabic nuclei and then extracting related phonetic features that are at the vocalic centers or syllabic nuclei. The system then uses such features to represent the sequential acoustic and phonetic events at the centers or nuclei. A significant improvement in language identification is thus realized through the use of syllabic features.
Accordingly, a minimal learning or reliable recognition process may be used to obtain basic acoustical features at the syllabic level. Such a combination of marking or extraction yields sufficient language differences for reliable language identification, without the difficulties associated with other segmental approaches.
A further substantial improvement over prior-art systems resides in the invention's utilization of a known speaker identification/verification methodology as a base line system to identify a set of well-matched speakers in each language. The system of the invention then compares the "test" speech to such well matched speakers in each language and then determines the language of the test speech. As will be understood, the matching process minimizes the effects of speaker deviations among different speakers either within or between languages. Thus, during such a comparison, the system minimizes speech differences due two different speakers between the "test" speech and the reference data.
Several scoring techniques are also implemented in the invention to minimize the effect of remaining speaker variations on language identification reliability.
Herein, a novel language identification system has been described with operates by finding the closest match of a test utterance to multiple speaker sets. Because the language identification system operates on spectral features at the syllabic level of speech, rather than at the frame level, this language identification system substantially exceeds the level of reliability achieved by prior-art language identification system. In experiments conducted by the inventor, the system of the invention typically achieved an improvement in decisional accuracy on the order of 15 to 20 percentage points relative to prior art language identification systems.
Although the present embodiment of the invention has been described in detail, it should be understood that various changes, alterations and substitutions can be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
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|Muthusamy, Y.K. and Cole, R.A., "Automatic Segmentation And Identification of Ten Languages of Telephone Speech," Proceedings of ICSLP, pp. 1007-1010 1992.
|Muthusamy, Y.K. and Cole, R.A., Automatic Segmentation And Identification of Ten Languages of Telephone Speech, Proceedings of ICSLP, pp. 1007 1010 1992.
|Savic et al. "An Automatic Language Identification System," ICASSP '91, pp. 817-820.
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|Spanias et al; "Speech Coding & Speech Recognition Technologies; A Review," 1991 IEEE Symp. on Circuits & Systems, 1991, vol. 1, pp. 572-577.
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|Sugiyama, M., "Automatic Language Recognition Using Acoustic Features," ICASSP-91, pp. 813-816, 1991.
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|Zissman, M.A.,"Automatic Language Identification Using Gaussian Mixture and Hidden Markov Models," ICASSP-93, RAA.8, 1993.
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|Sep 19, 2005
|Dec 28, 2011
|Oct 27, 2010
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|U.S. Classification
|International Classification
|Cooperative Classification
|European Classification
|Jul 20, 2000
Owner name: MICRON TECHNOLOGY, INC., IDAHO
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:ITT INDUSTRIES, INC.;REEL/FRAME:010977/0799
Effective date: 19991215
|Apr 26, 2001
|Fee payment
Year of fee payment: 4
|Apr 19, 2005
|Fee payment
Year of fee payment: 8
|Apr 15, 2009
|Fee payment
Year of fee payment: 12


text:
Apply online for eDM Recruitment, Government of Telangana
|Name of the post
|District Manager
|No. of Vacancy
|Rs 25,857/ month (all inclusive) with progressive increase per year.
|Age Limit
|24-35 yrs
|Educational Qualification
|- Any Graduate with Technical qualifications
- Min. of 2 yrs exp. in IT/ eGovernance/ IT related project Coordination and Program Management.
- Proficient in Verbal and written communication in English and well versed with local language
- Resident of same district.
Desired Skills :
- Prior Project Management exp.
- Exp. in IT projects, IT Infrastructure Deployment, Software Development, Hardware, Networking, Security, Security Management in IT projects/ IT enabled Service Project Coordination.
- Good people Management skills.
- Result oriented and self motivated for working in rural areas and cross reporting structure.
- Exp. in eGovernance related projects of organization/ Dept. NGO/ Non-profiut organizations.
- Willingness to travel across the district at the Gram Panchayats
Selection Procedure : The selection criteria will be based on the marks obtained in graduation, work exp., ICT certificates and marks in the interview. Candidates will be called for interview in the ratio of 1:10
How to Apply : Candidates can apply online through the link given below http://www.eseva.telangana.gov.in/cscrecruitment/
Application Submission Last Date 15-Nov-2016 on or before 07.00 pm.
* Please refer to the official Website or Employment Notice
Related Recruitment in the field of - Government jobs for Graduate,
Copyright Protected 2017 - Employment News In India | Indian Government Jobs

subset: commoncrawl


text:
Weaving Destiny (The Soulkeepers #2) by GP Ching and Giveaway!
Posted by Krystal Larson at 6:00 AM Thursday, September 22, 2011
Malini Gupta thought Jacob Lau was her destiny. But after months of failing to decipher how she fits into the Soulkeepers, frustration threatens to tear their relationship apart. And it doesn't help that a new Soulkeeper named Mara is ready to stop time itself to earn Jacob's love.
When Malini faces her worst fears, and even death, she learns a funny thing about destiny. Fate is a tapestry of choices, and she has the power to weave hers.
Goodreads Summary
This book picked up right where the last one left off. Malini is the main character, she is the reader's guide. This book is almost more concerned with Malini's potential relationship (or loss of relationship) than the plot of the first novel. Mara is the new girl, she appears to be trying to steal Jacob's affections and will do anything to catch his attention. Malini is understandably not pleased. She goes to great, at times almost humorous, lengths to prevent any love between the other two.
Malini is a fun character, she entertains the reader. She is smart, caring, and humorous. Jacob is still brave, sometimes a tad standoffish, and smart. Mara is a little bit of an annoyance-especially to a reader rooting for Malini.
The events are fairly fast-paced, the book ends in an interesting way, and the plot if just as good as before. This book is recommended to young adults/teens.
4 Stars
Giveaway: Leave a comment with your email address, one extra entry to GFC followers. This is INTERNATIONAL-ebook.
4 comments:
Julie said...:
I just got the first book in this series, and I would LOVE to win a copy of this one so I can read them one right after the other :D
jwitt33 at live dot com
Julie said...:
I am a GFC follower: Julie Witt
jwitt33 at live dot com
chelseacarson1 said...:
I am a GFC follower: Chelsea Carson
chelseacarson1 said...:
I read the review and now have to read this book. I need to find out what happens between Malini and Jacob!!!
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UK Dating
I would like to have my profile permanently deleted and my subscription cancelled I have met a lady on The Dating Group and we are... more..
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Cheryl Fergison marries fiance Yassine Al-JermoniPosted on: May 23, 2011 17:08:32
Single people looking for large ladies using bbw dating could be happy to hear Cheryl Fergison has married her fiance.
The 46-year-old EastEnders actress married her latest love, shop-keeper Yassine Al-Jermoni, in a secret ceremony in April.
Keeping the nuptials under wraps, the new husband and wife were wed in 26-year-old Jermoni's hometown of Agadir in Morocco.
Al-Jermoni, who is Fergison's second husband, was unable to return to the UK with his new bride as he does not have a visa to allow him to live in the country.
Fergison, who has a 12-year-old son from a previous marriage, rose to fame playing Heather Trott in the popular BBC soap opera.
Known for being unlucky in love, Trott has suffered a number of heartaches at the hands of characters such as Garry Hobbs and Minty Peterson.
Audiences were in a state of shock in 2009 after Fergison's character gave birth to the baby of 18-year-old Darren Miller.
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They may have been shackled together when they entered the house but Lee Ryan and Casey Batchelor have done anything but drift apart since they were set free In fact...
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Network Engineer
Phoenix , Arizona
November 24, 2016
3-5years' experience working with an IT Network infrastructure environment that includes experience working in various levels of management to successfully manage timelines, installation deliverables, and end user expectations.
3 years of experience with server class hardware and storage systems.
Demonstrated experience with Microsoft Hyper-V software. Limited administration experience with Microsoft SQL 2005, 2008 & 2012. Microsoft Exchange 2010, Microsoft SharePoint, and Microsoft System Center Operations Manager (SCOM).
Experience serving as a liaison between the business community and an Information Technology department.
Experience providing well written communications and management reports.
High School diploma or equivalent.
Current or recent Cisco Education or Certification is required.
Bachelor's degree in Computer Science, Computer Information Systems, Business, or a related field
An equivalent combination of education and job-related experience may substitute for the degree requirement on a year for year basis.
Proven experience with Microsoft WINDOWS 7 system administration, installation and on-going maintenance.
Cisco-CCNA Data Center (CCNA-Data Center)
Cisco Switch 45xx/37xx, routing, Layer2/3, VLANs, IP Routing, LAN and WAN.
Manage WAN/Routing/ACLs/Policies and VLANs.
Information Security and HIPAA.
Voice Over IP.
Storage Area Networks and Fiber Channel switching.
Monitor and report on network utilization, bottlenecks, and routing of multiple location infrastructure.
Some experience with Windows Server 2008/2012, Active Directory, DNS, DHCP, Group Policy, Exchange 2010/2013, and Microsoft Hyper-V Virtual Hosts/Servers.
Possess the ability to effectively troubleshoot systems, provide users technical support, and make critical decisions on the use of limited premier support services.
Knowledge and familiarity with Hyper-V software and tools for file server migrations, troubleshooting and performance tuning. Interface with database administrators and other IT professionals to coordinate installation and maintenance of client server applications to support enterprise line of business systems.
Extremely detail oriented, proactive self-starter demonstrating a positive, willing attitude and excellent oral and written communication skills.
Demonstrate the ability to multitask, follow through on all assigned tasks, and exercise good time management skills.
Must be able to consistently meet or exceed expectations on projects and provide guidance on County policies to other departments.
Exhibit skills required to embrace change and actively participate in planning short and long term goals to meet shifting business requirements.
Must be able to interact positively and effectively with staff members at all levels within the organization and work with management to resolve critical matters of significance that effect the team or customers.
Ability to adjust smoothly to changes in priorities and manages time effectively with little or no supervision.
Ability to provide on-call 24 X 7 services, visit data centers in different geographical locations, and apply system patches on the established monthly patch schedule.
About TEKsystems:
Join TEKsystems®, a leading IT staffing, IT talent management and IT services firm, and get your career on the fast track. We have more than 100 offices worldwide, and we partner with over 6,000 clients and place over 80,000 consultants per year. At TEKsystems, we seek to understand our consultants' skills, goals and interests, allowing us to present targeted job opportunities on a contract, contract-to-hire or direct placement basis. TEKsystems' leadership in the market stems from our sincere and personal commitment to driving the success of our customers, consultants and each other.
The company is an equal opportunity employer and will consider all applications without regard to race, sex, age, color, religion, national origin, veteran status, disability, genetic information or any other characteristic protected by law.
If you would like to request a reasonable accommodation, such as the modification or adjustment of the job application process or interviewing process due to a disability, please call 888 472-3411 or email firstname.lastname@example.com for other accommodation options.
A little about us:
TEKsystems provides corporations with IT staffing, talent management expertise and IT services, enabling them to meet their business objective.
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text:
Cynthia Nixon talks marriage ruling
Cynthia Nixon has revealed her excitement over same sex marriage being made legal in all 50 states of America, but insists the campaigning for equality for all couples must never stop.
History was made earlier this week when the Supreme Court of the United States voted to make same sex marriages legal in all 50 US states.
But Cynthia, who wed wife Christine Marinoni in 2012, has urged campaigners not to sit on their laurels now that this decision has been made.
In a guest column for Variety magazine, Cynthia referenced the groundbreaking progress last month in Ireland, where they became the first country in the world to legalise same sex marriages by vote.
"Of all the victories and defeats we've seen, nothing has been more inspiring than that victory in Ireland," Cynthia wrote. "That took everyone's breath away.
"Equality proponents knew they were going to win, but didn't take it for granted for a moment; they worked, they organised, leaving no stone unturned. And to have the vote come from the general population was absolutely game-changing. "The important thing to remember going forward, though, is no outcome is ever 100% assured. We have to keep organising like our lives depend on it."
Cynthia officially came out as bisexual in 2012, after previously hinting at her sexual orientation during an interview in 2007.
In the column, the mother-of-two stressed just how important it is to be open about your sexuality.
"LGBT characters aren't new; everybody has LGBT people in their family," she continued. "And everybody needs to make the effort to come out in any and every way they can. If people who are opposed to equality realised how many individuals they already like, admire or even love are LGBT, the battle would be over. It's important to come out to our parents, children, co-workers, boss — you name it."
© Cover Media


text:
|Chaz Bono
|Full Name
|Chaz Bono
|Male (FTM)
|Date of Birth
|March 4, 1969 (age 47)
|Eye Color
|Hair Color
| Cher (Mother),
Sonny Bono (Father, Deceased)
|First Episode
|Tonight, Tonight (1228)
|Last Episode
|Tonight, Tonight (1228)
|He was not shown again.
|Portrayed By
Character History
Season 12In Tonight, Tonight, Chaz was a judge for the competition while he was on break from his book tour. He tells the competitors that they're looking for star quality, great music, and orginality. Later at the competition, Adam Torres goes to talk to him after he gets WhisperHug disqualified for punching a member of a rival band. Adam tells Chaz that he got into a fight because he was made fun of for being FTM, which Chaz tells him isn't an okay reason to fight.
Adam tells him that he's messed up everything for a girl, and Chaz asks for the name of the girl, to which Adam says is Becky Baker. Chaz tells Adam that love is messy and to not blame Becky for her parents' attitude. Adam tells Chaz that he is his idol, and Chaz says that Adam is personally his idol for being this far along in high school. Chaz agrees to talk to Bullfrog Goldsworthy about allowing WhisperHug to perform back on stage.


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Cooled to an amazingly low temperature, the Protea chills the air simply by flying through it. Apparently, it gets colder the larger it grows.
This folk is only available with Keats and can be acquired from the Netherworld Core.
Protea's Data
Attack Type
Mid-range, Ice element area attacks. Continuous icy breath while button is depressed. Can direct breath from side to side during attack.
Karma Release
- Defeat 3 Bougainvaillea - Attack Power increased
- Use 5 Cold Tree Nuts - Attack Power increased
- Absorb 5 Protea Ids - Effect Area increased
Item Drops
- Green Dust (15%)
- Experience Points: 35
Recommended Strategy
Protea floats high in the air and has a huge ice attack that will cause a lot of damage, so attack Protea before it can do anything. If Protea is not beaten quickly, it calls in lots of Protta and will eventually leave.
Defeating Protea is fairly easy, just use Agapanthus to spam Fire attacks. The problem comes when trying to absorb the Id. It takes about four hits from Agapanthus to get Protea's red Id to appear but it may take upto five seconds before it actually pops out for you to absorb. This makes it very easy to overlook and a certain amount of 'trial and error' is needed to get it right.
|Navigate Folks
• By Element
• By Character:
— Keats


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If an item you ordered from TextbookRush does not meet your expectations due to an error on our part, simply fill out a return request and then return it by mail within 30 days of ordering it for a full refund of item cost.
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Description: A chorus of voices tells the story of the Africans who mutinied on board the slave shipAmistad.Written over twenty years, this poetic epic-part libretto, part captivity epistle-makes the past present, and even its sorrows sing. In "Buzzard," the opening section, we hear from the African interpreter for the rebels, mostly from Sierra Leone, who were jailed in New Haven. In "Correspondance," we encounter the remarkable letters to John Quincy Adams and others that the captives wrote from jail, where they were taught English and converted to Christianity. In lines profound and pointed, the men demand their freedom in their newfound tongue: "All we want is make us free." The book culminates in "Witness," a libretto chanted by Cinque, the rebel leader, who yearns for his family and freedom while eloquently evoking the Amistadsrs" conversion and life in America. As Young conjures this array of characters and their music, interweaving the liberation cry of Negro spirituals and the indoctrinating wordplay of American primers, he delivers his signature songlike immediacy at the service of a tremendous epic built on the ironies, violence, and virtues of American history. Heaven ainrs"t the end- Heaven begins the steady lifting. Things I donrs"t have no word for- bones lining the ocean floor. Hush, child. The rain. My voice all I carried. -from "Choir (Evening)"
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Capital Improvement Project Manager
Heery International, Inc. in association with Dukes, Edwards, and Dukes,
999 Peachtree Street, NE, Atlanta, GA 30309
2700 Promenade Two
1230 Peachtree Street NE, Atlanta, GA 30309
Associate Architect
Studio 3 Design
1617 Walton Way, Augusta, GA 30904
General Description
Location: Augusta, Georgia
Date Bid: July 2010 Construction Period: Oct 2010 to Sep
Total Square Feet: 214,000
Site: 1.82 acres. Number of Buildings: One; 668 parking
Building Size: Ground floor, 35,600; second floor, 35,600; floor
three thru six, 35,600; total, 214,000 square feet.
Building Height: Ground floor, 14'; floor three thru six, 10'6";
total, 75'2".
Basic Construction Type: New/Precast.
Foundation: Cast-in-place, pier & grade beam, auger cast piles.
Exterior Walls: Precast. Roof: Metal. Floors:
Concrete, precast. Interior Walls: CMU, precast.
Construction Team
Structural, Mechanical & Electrical Engineer: Johnson Laschober &
Associates - 1296 Broad Street, Augusta, GA 30909
Construction Manager at Risk: JE Dunn Construction - 800 Mount
Vernon Highway NE, #200, Atlanta, GA 30328
Civil Engineer: Cranston Engineering Group - 452 Ellis Street,
Augusta, GA 30901
A number of creative, innovative and technologically advanced solutions
were implemented to modernize Augusta-Richmond County's infrastructure.
Over time, the government predicts many of those upgrades will deliver
cost savings far greater than the original expenditure. Heery's role as
lead adviser to the client on design and construction issues resulted
not only in significant short-term cost savings across projects, but
also in smart long-term recommendations.
The Reynolds Street parking garage was initially designed to provide
parking for the Augusta Convention Center, which is being built across
Reynolds Street. The 650-space, $12 million parking deck was paid for
with a 3-cent local car rental tax and special-purpose local-option
sales tax funds. Designed to respect the style of surrounding historic
buildings and to blend in with the downtown's existing architecture, the
parking garage is one of several building projects in the county either
completed or in the works.
Facing a backlog of voter-approved Special Purpose Local Option Sales
Tax (SPLOST) projects that needed to be guided to completion,
Augusta-Richmond County selected Heery to oversee renovations to some of
the consolidated city-county's most noteworthy structures, as well as
several new construction projects. Projects include the expansion of the
county jail, design and construction of a new main library, new judicial
center, exhibition center and Sheriff's Administrative Headquarters; and
renovations to the Municipal Building, and the Augusta Museum of
History. The program, which began in 2004, is slated for completion in
Product Information
Precast: Metromont
Metal Roofing: Petersen
Lighting: Lithonia
Curtain Wall, Entrances & Storefronts: YKK
Elevators: Otis
©2015 Copyright DC&D Technologies, Inc. All rights reserved. | DCD
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PICS: One hospitalised after single car crash in north Dublin
One person was taken to hospital in north Dublin last night after a single vehicle crash.
Dublin Fire Brigade have posted images from the scene of the smash which the Finglas Station attended to in Kilbarrack.
Our Finglas fire engine & ambulance from Kilbarrack attended this single vehicle RTC in Santry last night. 1 to hosp with spinal precautions pic.twitter.com/cxz72b3blR— Dublin Fire Brigade (@DubFireBrigade) November 9, 2016
More to follow...


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After the shakedown, Red Bull Skoda can go into the Rally of Turkey in Antalya very confidently The source of error from Cyprus was localized and remedied in both Fabia WRCs Accordingly, today's runs were positive ones: Both Harri ...
After the shakedown, Red Bull Skoda can go into the Rally of Turkey in Antalya very confidently
The source of error from Cyprus was localized and remedied in both Fabia WRCs
Accordingly, today's runs were positive ones: Both Harri Rovanpera/Risto Pietilainen (FIN) and Andreas Aigner (AUT)/Klaus Wicha (GER) were able to complete this performance check successfully.
The great unknown of this WRC event is the weather: For the next two days, incessant rain has been forecast
After the inexplicable retirements in Cyprus, Red Bull Skoda was able to get clear about the causes of their problems during an additional test day in Turkey on Monday. An engine specialist had been flown in for that reason, who together with the team got to the bottom of things. It was determined that faulty electronics were the indisputable cause, the sensors relaying wrong data to the engine control unit. Neither engine was damaged in the course of this.
This was confirmed during today's 5.5 kilometre shakedown, ten kilometres south of Kemer. Both Fabia WRCs ran immaculately and provided the team and both drivers with positive results.
Harri Rovanpera was able to achieve the eighth-fastest time without taking a risk: "I'm very glad that we can start this rally now after solving our problem. So my target is clearly set, I really want to bring in drivers' and manufacturers' points."
Andreas Aigner looks forward to his rally with a lot of confidence as well: "I ran the shakedown only twice, this was enough to determine that we can go into the rally with a lot of optimism. But the weather conditions, with plenty of rain, should make for a very tough rally."
The weather has already claimed its first victims. In yesterday's evening hours, a thunder-storm raged over Kemer. Many tents in the service park were simply torn away, the total damage amounting to millions. Red Bull Skoda was not spared either and lamented the total loss of two service tents.
Armin Schwarz, one of the team bosses together with Raimund Baumschlager, was a guest of the official FIA press conference today: "The rally itself is very difficult to assess. The weather is going haywire at the moment, so everything's possible right now. A lot can happen during those three days, I just hope that our team is able to complete a positive rally."
-credit: www.redbullskoda.com


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|Sam Robards
|...as Daniel Hendricks
Daniel Hendricks/Paul Whitlock/Davis Webb
|Date of birth
16 December 1961
|Place of birth
New York City, New York
|...as Paul Whitlock
|IMDb profile
Sam Robards is an actor who played two different characters in Law & Order and Law & Order: Criminal Intent. He played Daniel Hendricks in the Law & Order season four episode "Apocrypha" and Davis Webb in the L&O Season 20 episode "Fed". He also played Paul Whitlock in the Criminal Intent season four episode "Magnificat".


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Samsung's Ativ Tab 3 is the world's thinnest Windows 8 tablet at 8.2mm, and like the Samsung Ativ Q it also boasts the excellent S Pen stylus for getting creative on the go.
The slender frame weighs 550g which is comparable to Apple's iPad, although the Ativ Tab 3 isn't anywhere near as chunky as Apple's tablet. It certainly isn't a light device, and we can tell our arm would ache if we clutched it one-handed for the length of our commute, but at least you can easily slip it into a bag or case to carry around. While the 8.2mm thickness is eclipsed by the incredible slender design of the Sony Xperia Tablet Z (6.9mm), it's still an impressively thin build finished off with an attractive while-and-silver finish.
The Ativ Tab 3's 10.1-inch screen packs a 1366 x 768 resolution, which is standard for a tablet this size. We had a brief play and it's typically strong for a Samsung display, with great viewing angles and enough power to counter harsh lighting. A micro HDMI slot also allows you to hook up to a TV, if you want to share movies, apps and so on with the rest of the family.
S Note 2.0, the updated version of Samsung's stylus software, comes pre-installed on the Ativ Tab 3 so you can get the most of the handy S Pen (which slips into a corner slot so you don't lose it when not in use). You also get a free copy of Office, which gives you a great range of productivity software – great news if you need to keep working on the train home.
An Intel Atom processor runs the show, backed up by 2GB of RAM. A mighty 64GB of storage allows you to install tons of apps or carry lots of music and movies around, and you also get a Micro SD memory card slot for expansion.


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Green Party Leader Peter Bevan Baker speaks to reporters after throne speech in this Guardian file photo.
©Guardian photo by Brian McInnis
Premier Robert Ghiz's assertion that his biggest mistake as premier was bringing in fixed election dates has caught the ire of Green party Leader Peter Bevan-Baker.
Bevan-Baker argues the province's democratic institutions were designed to ensure the will of the people is reflected in the legislature.
"The Westminster style of democracy we adopted here in Canada came from a desire to take power away from an unopposed monarch and pass it to the people. Over centuries we have arrived at the electoral system we now use where every adult citizen has an opportunity every four years or so to elect the people they prefer to make our collective decisions," Bevan-Baker said.
"The painful irony of our current situation on P.E.I. is that by political sleight of hand, Liberals, in crowning King Wade (MacLauchlan), are effectively restoring the unrestricted regal power our democracy sought to eliminate," said Bevan-Baker.
He pointed out Alberta, which currently has a similar political situation to P.E.I., has seen no need to return to the polls to allow their new premier Jim Prentice to seek a mandate.
"The P.E.I. Liberal attempts to explain the 'need for an election' are all bogus nonsense, and have no basis in democratic principles. I only wish that more Islanders would recognize it for what it is naked political opportunism," said Bevan-Baker.
For Premier Ghiz to call fixed election dates his 'biggest mistake' in the context of PNP, Plan B and the Geosweep debacle, is baffling to say the least, he added.
Fixed election dates are a definite improvement to our democracy - they even the playing field, remove political opportunism available to governing parties and allow all parties to prepare financially and otherwise, Bevan-Baker asserts.
They also encourage a wider array of potential candidates to come forward, he said.
Far from Ghiz's biggest mistake, Bevan-Baker believes fixed election dates could be looked upon as one small glimmer of good governance.
"How about a New Year's resolution for all Islanders to give up once and for all a really bad habit, one that we have developed over many elections and passed from one generation to the next. Let's quit voting for people and parties who, above all, look after themselves, and have consistently let us down," he said.
"It's time to elect parliamentarians who will carry out their roles as they were originally designed to represent their constituents first and foremost, and abandon mindless slavery to their party."


text: Dreamsinger LegguardsBinds when equippedMailLegs179 Armor+5 Spirit +8 Stamina +8 StrengthDurability 80 / 80Requires level 21 SourceEdit This article or section is an item stub. You can help expand it by editing it. Item boilerplate · Boilerplate help · Research: Wowhead WoWDB Use {{Stub/Object}} for objects that are fixed in place. External linksEdit Battle.net (EU) Wowhead Thottbot WoWDB Retrieved from "http://wowwiki.wikia.com/wiki/Dreamsinger_Legguards?oldid=2580464" Ad blocker interference detected! Wikia is a free-to-use site that makes money from advertising. We have a modified experience for viewers using ad blockers Wikia is not accessible if you've made further modifications. Remove the custom ad blocker rule(s) and the page will load as expected. Categories: Item stubs World of Warcraft mail legs items World of Warcraft rare items Add category Cancel Save


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Snowboarding News | Sunday December 16, 2012 | Shared By: Arapahoe Basin
It started about 6:30 this morning. About 2-3" have fallen and now, at 11 AM, it is still snowing. While I don't think this is going to be huge dumper of a snowstorm, we are having very favorable winds ranging from Southwest to West to Northwest. All of those wind directions really favor 1st, 2nd, and 3rd Bowl, The Spine and The Face. As I speak there are patrollers ski packing and impacting Pali. Remember, both wind and snow make The Basin. While the new snow numbers won't be outrageous, the wind is good, and this storm will be a significant boost for North Side skiers.
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Account Executive Jobs In Illinois, United States
Browse For Account Executive Jobs In Illinois, United States. Find The Job Of Your Dreams On Variety Media Careers Today!
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- Tribune Company
- Moline, IL United States
- 07/25/2017
- Sales / Biz Dev
Overview: POSITION SUMMARY (Scope & Purpose)WQAD 8 has an opening for an Account Executive. Responsibilities include proposing media advertising strategies over several media platforms to local businesses and advertising agencies. Previous sales experience and a college degree preferred. Working... More Details
- Tribune Company
- Chicago, IL United States
- 07/25/2017
- Sales / Biz Dev
Overview: About Digital And Then Some "DATS" a division of WGN Radio & Tribune Digital:Digital And Then Some (DATS) is a turnkey digital agency that uses clients' visions to develop custom content of the highest quality. We live the mantra that "Content is King." By partnering with WGN Radio, yo... More Details


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Acne can be tremendously embarrassing, most especially, if you have a very special occasion like a date, meeting, interview, or worse your wedding. At such situations, you are desperate to get rid of that noticeable redness, blemishes or scars on your face caused by acne. There is no need to panic because here are very effective acne treatments that work overnight.
Egg Whites
Egg whites when applied on your face and left to dry overnight can help get rid of pimples. Upon waking up, you can wash your face with warm water. There is no need to use soap because it can lead to skin dryness. You can easily buy an egg from a store, and then you can separate the yolk and white from the whole egg manually.
Ice or Cold Pack
Applying ice or cold pack on your pimple can help remove it. It actually reduces inflammation and redness caused by acne. This is one of the best acne treatment choices according to FightAcneAtHome.com because it is free! You can do this for five to ten minutes before you go to bed at night. When you wake up, you will see the improvement.
Another effective acne treatment that works overnight is a slice of potato. A potato has components that are good for the skin. And they can effectively get rid of acne or pimple. When applied on the acne area, its starch can absorb the oils that clog skin pores. For 30 minutes, leave the potato on your skin.
Lemon Juice, Tea tree and Manuka Honey
Lemon juice, tea tree oil and Manuka honey are also three popular natural overnight treatments for acne. After cleansing your face before you go to sleep, you can apply any of the three natural remedies. You can wash your face and see the changes when you wake up.
White Toothpaste
White toothpaste is also known to treat zits. You can use your finger to apply it gently on your pimple and leave it overnight. It dries the pimples on your face; thus, heals them quickly. Some find it very effective to apply the cold pack first before the toothpaste.
Benzoyl Peroxide and Salicylic Acod
Lastly, certain over-the-counter acne products help get rid of zits overnight. Such products contain benzyl peroxide and salicylic. Carefully read the labels and instructions especially on the amount applied to your skin. It's important that you don't over-expose your skin to these chemicals because they can be damaging and it may take you a while to get it back to its original smoothness.
These are some acne treatments that effectively work overnight. Indeed, getting rid of pimples quickly is not that stressful if you know what to do. You can apply these treatments and say good bye to acne and pimples. With a smooth and pimple-free face, you can feel more comfortable about yourself all day and night.


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In 2012, registered nurses earned an average of $67,930 a year, according to the Bureau of Labor Statistics. But advanced certifications have a way of improving a nurse's earnings. A survey in "Nursing2013," a national nursing journal, found that those working in emergency medicine made $71,200 a year as of 2011. For those certified in emergency nursing, training often begins as it does for any other registered nurse.
Emergency room nurses, particularly those with emergency certification, must be registered nurses, explains the Board of Certification for Emergency Nursing. So, training begins in one of three ways -- through a bachelor's of science program, an associate degree program or a diploma program. As with any bachelor's degree, you're looking at a four-year commitment for a BS in nursing. Associate degrees and diplomas in this field can take from two to three years to complete.
No matter your choice of program, the coursework is pretty much the same. It's a combination of classroom and clinical experience. You'll cover topics such as health assessment, basic skills of nursing, anatomy and physiology, pediatric nursing and gerontological nursing, among others. For clinical experience, you can find yourself working in pediatrics, maternity, surgery and emergency clinics. Upon graduation, you'll sit for the National Council Licensure Examination, or NCLEX-RN, which allows you to practice as a registered nurse.
Although not a prerequisite, the Board of Certification for Emergency Nursing recommends two years of experience in the emergency department before sitting for the CEN, or Certified Emergency Nurse, exam. The two-year recommendation is largely due to the testing content. The exam tests candidates on cardiovascular, gastrointestinal, gynecological, maxillofacial and neurological emergencies, among other topics. A little on-the-job training in emergency medicine can prove beneficial to your certification.
Besides practical experience, CEN prep courses can help. These short training programs review the core topics of the exam, only covering Certified Emergency Nurse materials. But you'll walk away with a study book, study aids and continuing education credits -- something that can help registered nurses move into other positions within a hospital or clinic. Prices vary by program, but the fee runs around $250 as of 2013. Preparation exams and study materials are also available through the Board of Certification for Emergency Nursing.
- Bureau of Labor Statistics: Occupational Outlook Handbook – Registered Nurse
- Board of Certification for Emergency Nursing: CEN Eligibility FAQ
- Board of Certification for Emergency Nursing: CEN Review Courses
- Bureau of Labor Statistics: Registered Nurses
- Nursing2013: Nursing2011 Salary and Benefits Survey Report
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- Jupiterimages/Creatas/Getty Images