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Originally written on Project Spurs | Last updated 1/1/13
FOR SPORTS - Spurs' Tony Parker walks off the court after the Western Conference Playoffs First Round Game 1 against the Mavericks Saturday April 18, 2009 at the AT&T Center. The Mavericks won 105-97 Photo via Newscom
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As if battering the Dallas Mavericks for a 25-point blowout win wasn't enough, San Antonio Spurs guard Tony Parker rubbed salt in Dallas' wounds by finishing after being fouled deep into the Mavericks' defense. With just under four minutes remaining and the game put away for the night, Parker was fouled by Chris Kaman but hung on to bounce in the shot on his way down.The shot counted for two of Parker's game-high 21 points.
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Key West, FL - $10 1902 Date Back Fr. 617 The Island City NB Ch. # (S)7942. ...
2014 January 8 - 10 & 13 FUN US Currency Signature Auction - Orlando #3526
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Orange County Convention Center
9800 International Drive
Orlando, FL 32819
|Printable auction results for all items in the 2014 January 8 - 10 & 13 FUN US Currency Signature Auction - Orlando.
First Ever Offering From This Legendary BankKey West, FL - $10 1902 Date Back Fr. 617 The Island City NB Ch. # (S)7942
A simply extraordinary find, and quite probably the Florida discovery of the year 2014. It comes from a bank which issued Red Seals and Date Backs only during its ten year existence and is legendary amongst Florida collectors, playing the role of the Great White Whale, which might or might not be out there, leaving tantalizing clues to its existence but never quite appearing. The censuses are even divided as to whether another example exists, with the Kelly census stating that a single $5 Red Seal is known, but omitting its grade and bank serial number, while the newer and more definitive National Bank Note Census states only "No Records Found" when queried about the population for this bank. We can, however, say with some certainly that no collector now alive has had the opportunity to purchase a note on this bank until the hammer falls this evening. Whatever the number, there will only be one fortunate buyer who can boast that he has finally landed the "Big One" from this island city. PMG Choice Fine 15 Net, with mention of a restoration that affects nothing on a note of this rarity.
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You can indicate the ring size, special gift wrapping or any other request to the designer at checkout.
Ships with
DHL Express: 2 - 5 days from dispatch.
100% Japanese silk
79 inches x 32 inches
Various textures and weights of silk organza in one large scale shawl. The scarf expresses the image of the butterfly's wings landing on the flowers petals.
Flower printing in silk organza with three colors, using Japanese special shrinking technique. It has opaque areas and transparent areas which gives the depth of texture and drapes.
Yuh Okano's original technique with Japanese craft man. Soft and durable. Available colors; Beige-baby pink, Purple-blue , and pink-blue.
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EDITORIAL: Cheers, Jeers and Tears
Cheers for the always fun and colorful Frog Follies, being held for the 38th year this weekend at the Vanderburgh County 4-H Center on Boonville-New Harmony Road. Even if you don't go, you will know it is that special weekend by seeing all of the street rods on Evansville's streets this weekend.
Tears fall for Bill Wilder, a beloved Boonville street rod enthusiast who was the retired fire chief at Alcoa. He was the founder of A-Plus Rod & Kustom. which specialized in building custom street rods, something Wilder loved to do. He died August 17 at the age of 68.
Cheers for one of our own, former Courier & Press staff writer Roberta Heiman, who has been named recipient of the Albion Fellows Bacon Award. The award was presented Thursday by the Women's Equality Day Committee. After retiring from the newspaper, Heiman helped rejuvenate the League of Women Voters of Southwestern Indiana. She is now president of that organization and the Evansville-area Trails Coalition. She serves as well on the Evansville Parks Board.
Tears fall for Garey W. Patmore of Newburgh, one of the University of Evansville men's basketball team's most devoted fans, and one who felt strongly that the university should bring back football. Patmore, a retired insurance salesman, was a familiar and friendly face at UE athletic events.
Cheers for the news that award-winning civil rights activist Diane Nash will be the keynote speaker at this year's Evansville-Vanderburgh County Human Relations Commission's annual dinner on Sept. 19. Dr. Martin Luther King described her as the "driving spirit in the nonviolent assault on segregation at lunch counters." The theme this year is "Passing the Torch: Inspiring the Next Generation of Leaders."
Cheers for the return of the Great Lakes Valley Conference men's and women's basketball tournaments at the end of the coming season. The teams will compete at the Ford Center in Downtown Evansville. This will be the first time since 2007 that the tournaments will be held in Evansville.
Continuing jeers to the meth idiots in our city. This week a fire broke out in a vacant apartment building in the 400 block of south Kentucky Avenue, and fire officials say the signs are there. They say a meth lab-related fire broke out in the same building last year.
Cheers for all of the college students who have been returning to the University of Evansville and the University of Southern Indiana for the beginning of fall classes. It is always a good sign of life in our fair city to see these young people moving back to their college campus. They bring an energy that is not there when they are away for the summer. Cheers, as well, go to the students at Ivy Tech who are returning.
Cheers for the news that former Indianapolis Colts head coach Tony Dungy will speak on Dec. 6 at an Old National Bank event benefiting Youth Resources of Southwestern Indiana. He works now as an analyst for NBC sports.
Subscribe to the Courier & Press or The Gleaner
Need Help? Call us at 1-877-304-7771.
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No player would want it any other way, but there is an unintended consequence that comes with Archbishop Carroll's long streak of Catholic League girls' lacrosse titles.
"It actually puts some pressure on the girls," coach Lorraine Beers said. "No one wants to be the one that breaks it or loses the streak."
There was no need for worrying about that Thursday. Archbishop Carroll beat St. Hubert, 20-2, in the Catholic League semifinals at Neumann University.
Carroll will go for its 13th straight championship Monday against Cardinal O'Hara at Neumann at 6 p.m.
O'Hara advanced to the title game by beating Archbishop Wood, 10-5, on Thursday.


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Not quite a noob, Not quite a Pro, Not quite old man, Not quite boy racer......
View Single Post
Joined: May 2008
Location: NW Suburbs, IL
Oddometer: 3,668
I'll give that a whirl. We haven't used too much coconut water in smoothies, but have in some other cooking\baking recipes. As things progress, I'll figure out what works. Thanks for the tip!
I'm not a fan of drinking straight coconut water\milk, but it does make some tasty ice cream.
Who doesn't love casing doubles? I didn't commit on a smaller double at a neighbors track. Resulted in the following:
Broken linkage & snapped the shock in half.
And not sure if it was that, or catching my foot in a rut earlier that day, but I also had to get a giant syringe worth of blood pulled out of my knee. Oddly enough, the doc told me my knees looked in great shape.
I've been getting used to the heat now. And just like always, I'll get used to the heat & 2 weeks later, Illinois will get all crazy weather and it'll start snowing or something.
I could really go for some 65 & light drizzle riding right now though.
I'm a bit torn right now on getting a new bike. Mostly cause I hate to lose money on the Husky, and I surely would. And besides that, I really enjoy riding it. The thing has good power, feels good in the woods (though I need to do some work on the rear shock), and is overall a good bike...but apparently problematic. My wife has informed me she'd pick me up a new bike when she graduates from nursing school next August, so I've been tossing around the idea of a new GasGas. I know, I know....just get a KTM. I just can't do it. That and the new GasGas bikes just look wicked, and if they're anywhere near how my GasGas trials bike was....it'd have to handle like a champ.
Time to get some work done. I ordered up the wrong belt to fix one of our machines here at our shop. Let's hope I can find one locally. Happy Mondays.
Andrew Gore
Economy Cycle
Team MGH #205 - Midwest Harescramble Rambling
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Screen Printing and Stenciling Underglaze Designs on Curvy Pots
Today's video clip didn't quite fit onto the new Meredith Host DVD because we ran out of space. But I just couldn't bear having it languish on the cutting room floor, so I decided to share it with you all today. As we all know, transferring two-dimensional designs onto a three-dimensional surface can be challenging – especially if that surface is curvy. In this clip, Meredith shows how she approaches screen printed and stenciled decoration on one of her curvy mugs. – Jennifer Harnetty, editor.
Throwing and Decorating a Platter with Meredith Host
Meredith Host's wheel-thrown plates begin as large clay discs with lots of supporting clay, which allows her to get excellent compression to avoid cracks. The excess clay is lathed away at just the right time in the trimming process. She then explains and demonstrates how the continuous curve on the top surface of the plate not only makes a great canvas for decoration, but also helps in the structural support.
An Easy Way to Add Screen Printing to Your Decorating Repertoire
I love the look of screen printed images but I avoided trying screen printing on my clay work until I discovered a super easy way to make the screens using the sun as an "exposure unit." Now I have been having lots of fun experimenting with the technique. In today's post, an excerpt from her DVD Form, Pattern, and Underglaze, Meredith Host demonstrates how easy it is to make these screens and get started with screen printing on clay.- Jennifer Harnetty, editor.
How to Ensure Proper Cup and Saucer Fit
I love the making forms that go together, like salt and pepper sets, or cups and saucers. It is a fun exercise to come up with forms that relate and fit together, both functionally and aesthetically. If you have never tried it, give it a shot.
To get you inspired, I am presenting a clip from our newest DVD Form, Pattern, and Underglaze: Wheel Throwing and Decorating with Meredith Host. In the clip Meredith explains her method for getting a great fit on stacking cup and saucer sets.
Form, Pattern and Underglaze: Wheel Throwing and Decoration
In this installment of the Ceramic Arts Daily Presents video series, Meredith Host shares her techniques for creating wheel-thrown pottery to which she adds colorful underglaze decoration. Meredith throws several of her forms, explaining tips for success with each one. After the throwing demonstrations, Meredith leads you step-by-step through her decorating technique where you'll discover that getting colorful surfaces can add a whole new dimension to your pottery.
Pottery Video of the Week: Decorating Ceramic Forms with Screen Prints and Stencils
On Wednesday, we announced that Kansas City potter Meredith Host was the winner of the Peoples Choice Emerging Artist contest. Lucky Meredith gets a $500 gift certificate from the generous folks at Bailey Ceramic Supplies, who sponsored the contest! And lucky for all you faithful readers out there, we filmed Meredith demonstrating at the Potters Council Workshop Surface + Form a couple of months back. Today, we are sharing that video with you.


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Originally written on borisdiawtime.blogspot.com | Last updated 3/1/12
San Diego Chargers 2011 Record: 8-8 PPG For: 25.4 (5th) PPG Against: 23.6 (22nd) 2012 Cap Number: $111,960,165 Draft Position: #18 Pick Masochist: A person who is gratified by pain, degradation, etc., that is self-imposed or imposed by others. Let me tell you something; when you voluntarily bring Norv Turner back despite massively underachieving with what is clearly the most talented team in your division, you are, by definition, a masochist. Because while this is certainly not the same team that won 14 games under Marty Schottenheimer, it has way too much talent to miss the playoffs two consecutive years. The job Norv has done is completely and utterly unforgivable – except that we've already established that the Chargers top brass are all masochists. They must love the pain of seeing lesser teams win the AFC West. They must love degrading themselves to the level of the Raiders and Cardinals. And yes, it's all self-imposed. The day they decided that Norv Turner would be a better choice than Marty Schottenheimer was the day the Chargers franchise ceased to be relevant.
All that having been said, the AFC West is so pathetic that even Norv Turner might be able to win it this year. If the Chargers can retain the majority of their offensive talent and retool the defense, they will likely be the favorites once again. Doesn't mean they'll actually win anything – we know how good Norv is at underachieving! – but it does at least make them worth talking about. For now.
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text:
11 Practice Tests for the SAT & PSAT 2014 (Paperback)
|Author: Selena (EDT) Coppock
Learn more about 11 Practice Tests for the SAT & PSAT 2014:
Format: Paperback
Publisher: Random House Inc
Sku: 243391914
Publish Date: 7/2/2013
Dimensions: (in Inches) 11H x 8.5L x 1.75T
Pages: 944
See more in SAT
From the Publisher:
THE PRINCETON REVIEW GETS RESULTS. Get all the prep you need to ace the SAT and PSAT with 11 full-length practice tests, comprehensive explanations for every question, and helpful scoring grids and admissions advice.
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The Triumph Register of Southern California
Main Navigation
TRSC Home Page
Page 2 Events Listing
Page 3 Contact Info
Page 4 TRSC Club News
Page 5 Member Photos
Page 6 Event Photos
Page 7
Page 8 Car Club Network
Page 9 Proposed By-Laws
Page 10
TRSC is dedicated to the preservation, operation, and enjoyment of Triumph automobiles.
Welcome to TRSC!
We've been having fun with Triumph Cars since 1977: jump in yours and come join us!
Monthly Meetings:
4th Tuesday night of each month
except November, which is on the 18th this year. No December meeting.
Maggie's Pub, 11900 Telegraph Road, Santa Fe Springs, CA.
Near the 405 & 605 interchange. 6:30 PM for dinner, 7:30 PM for club business. For directions
click here:
Weekly Regional Meetings:
First and Third Saturday mornings: "San Fernando Valley Breakfast Club"
Held at the World Famous Bob's Big Boy
at 4211 W. Riverside Drive, Burbank, CA.
Breakfast about 9:00 AM, get there about 8:30 for tire kicking and bench racing.
Contact Info:
Dale Berman
818 841-0200
Second Saturday Mornings: "Orange County Breakfast Club"
Watson's Drug, SE corner of the Orange Traffic Circle
, on Chapman. Breakfast from 9:00 AM - 11.00 AM
Note: the world famous 'Cars & Coffee' at the Ford Design Center has been suspended due to high turn-out.
There is a new 'Cars & Coffee Orange County' in the planning stages, and we are waiting for that. In the meantime we will continue to have a 'show' before the drive and breakfast: check our Facebook page for fast breaking details!
Caravan from there to breakfast on twisty Triumph roads in the foothills, or just meet us for breakfast. Your choice!
Contact Info:
John Gladysiewicz 714 838-9148
Both breakfast clubs meet regardless of weather or conflicting events.
TRSC Membership Information:
Yearly dues are still only $35.00
Mail your check to -
Heide van den Akker
TRSC Membership Secretary
1159 Tivoli Lane #87
Simi Valley, CA 93065
805 522 2123
Membership includes weekly e-mails, our award winning direct mail newsletters, tech help, meetings, events, and more!
For a printable PDF copy of the
Membership Application please e-mail email@example.com.
Publishers of "The Triumph Tribune", The Official Journal of TRSC
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Hundreds of photos, major event notices, last minute changes: see your car here!
Followers from around the globe!
Facebook.com, search: "TRSC" or
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Events page provides automatic updates Photo galleries:
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TRSC logo
patches, windshield decals, grille badges, license frames, and name tags: see page 4.
Contact Abel Miramon: amiramon@sbcglobal, or 626 571 2550
Questions? Tech help? Parts needed or for sale?
Contact Steve at
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text:
Hands-free phones with voice activity detection using a comparison of frame power estimate with an adaptive frame noise power estimate, automatic gain control with fast adaptation and minimal speech distortion, echo cancellation updated in the frequency domain with stepsize optimization and smoothed spectral whitening, and echo suppression with adaptive talking-state transitions.
1. A process of echo suppression, comprising:
A. updating, for every received and sent frame of voice data, and in a range of zero to a maximum value:
i. a count in a first hangover counter for an Idle operating state,
ii. a count in a second hangover counter for an Double-talk operating state,
ii. a count in a third hangover counter for an Far-end talk only operating state,
iv. a count in a fourth hangover counter for an Near-end talk operating state, and
v. the updating including updating the counts in the counters at a change of operating states with one of an increment/decrement updating, a quick updating, and a time-delay updating;
B. computing each of four coefficients as the relative counts of the respective first, second, third, and fourth hangover counters;
C. computing attenuations for a receive amplifier and a send amplifier as linear combinations of the four coefficients;
D. attenuating amplification of a received frame of voice data to be applied to a speaker, and attenuating amplification of a sent frame of voice data from a microphone to suppress echoes.
2. The process of
3. The process of
4. The process of
5. The process of
6. The process of
7. The process of
8. The process of
Priority is claimed from provisional Appl. No. 60/582,953, filed Jun. 25, 2004. The following co-filed US patent applications disclose related subject matter and have a common assignee with the present application: application Ser. Nos. 11/165,902; 11/165,903; and 11/165,898.
The present invention relates to signal processing, and more particularly to voice activity detection, automatic gain control, echo cancellation, and echo suppression devices and methods.
Hands-free telephones (e.g., speakerphones) provide conveniences such as conversations while driving an automobile and teleconferencing with multiple speakers at a single phone. However, acoustic reflections of the loudspeaker output of a hands-free phone to its microphone input simulate another participant speaker and thus appear as an echo to the original remote speaker. Acoustic echo cancellation and echo suppression attempt to minimize these effects.
Acoustic echo cancellation methods approximate the properties of the loudspeaker-to-microphone acoustic channel and thereby can generate an approximation of the microphone pickup of sounds emitted by the loudspeaker. Then this approximation can be cancelled from the actual microphone pickup. Acoustic echo cancellation typically uses adaptive filtering to track the varying acoustic channel; see Dutweiler, Proportionate Normalized Least-Mean-Squares Adaptation in Echo Cancelers, 8 IEEE Tran. Speech Audio Proc. 508 (2000).
However, long echo paths (e.g., 400 ms) at high sampling rates (e.g., 16 KHz) leads to filters with a large number of taps (e.g, 6400). This makes the complexity of the filter convolution very high, so frequency domain techniques are often used in these applications; see J. Shynk, Frequency-Domain and Multirate Adaptive Filtering, IEEE Signal Processing Magazine 14 (January 1992). Frequency-domain multiplication is much cheaper than time-domain convolution, and the signals can be efficiently transformed from time domain to frequency domain by Fast Fourier Transforms (FFTs).
Since the Fourier Transform of a long echo path can be too large for practical situations, partitioning the echo canceller filter into smaller subfilters allows the use of shorter transforms; see C. Breining et al, Acoustic Echo Control, IEEE Signal Processing Magazine 42 (July 1999).
Estimation of the echo residual after echo cancellation allows for echo suppression by gain adjustment. Echo suppression may be applied to degrees of full, partial, or half-duplex communications; see ITU-T Recommendation P.340 Transmission Characteristics and Speech Quality Parameters of Hands-free Terminals (May 2000) and ETSI TR 101 110-GSM 3.58 Digital Cellular Telecommunications System: Characterization Test Methods and Quality Assessment for Handsfree Moblie Stations v.8.0.0 (April 2000).
In general, a hands-free phone provides automatic gain control (AGC) to make the loudspeaker output voice level match a user-specified target level. The goal of AGC design is to adjust the voice level as fast as possible while minimizing the output signal distortion (e.g., peak clipping). Also, the AGC should be designed to avoid excessively amplifying background noise (silence intervals). A voice activity detector (VAD) helps the AGC avoid amplifying background noise. The common usage of VAD for the AGC is to adjust the voice level when the VAD decision indicates voiced input (speech intervals) but to leave the gain-scaling unchanged when the VAD decision indicates unvoiced input (silence) intervals). A problem with this method is that the VAD decision error could cause audible distortion in the output speech. An accurate VAD could minimize the decision error, but it may require a complicated algorithm, and in turn, higher computational complexity; see for example, P. Chu, Voice-Activated AGC for Teleconferencing, Proc. IEEE ICASSP 929 (1996).
The present invention provides echo suppression with adaptive state transitions.
1. Overview
A voice activity detector (VAD) provides a decision whether a frame contains speech or silence (or marginal speech activity).
Preferred embodiment echo cancellation simulates the microphone's pickup of the loudspeaker output by estimating the corresponding acoustic channel by an adaptive filter with one or more of the features of (i) an optimal adaptation stepsize, (ii) frequency-domain adaptation computations including smoothed spectral whitening, (iii) adaptation stepsize control according to filter misadjustment and frame echo-to-noise, and (iv) the filter partitioned into subfilters with frequency-domain adaptation stepsizes proportional to subfilter energies.
The preferred embodiment methods can be performed with digital signal processors (DSPs) or general purpose programmable processors or application specific circuitry or systems on a chip such as both a DSP and RISC processor on the same chip with the RISC processor controlling. A stored program in an onboard ROM or external flash EEPROM for a DSP or programmable processor could perform the signal processing. Analog-to-digital converters and digital-to-analog converters provide coupling to the real world, and modulators and demodulators (plus antennas for air interfaces) provide coupling for transmission waveforms. The speech can be encoded, packetized, and transmitted over networks such as the Internet.
2. Voice Activity Detector
First, presume a sampling interval of T, so time t is expressed as integer n with t=t0+nT where t0 is an initial time. Let r(n) be the input sample at time n and rN(n) denote the VAD observation vector; that is, at time n the last N samples:
Next, for frame time m (the time t0+mNT at the start of the mth frame) define the frame power estimate, pr(m), as the average sample energy over the last N samples:
Similarly, define the frame background (white) noise power estimate, pw(m), with an adaptive estimate of the minimum energy level of the current frame energy. The noise power estimation uses an asymmetrical gain which decreases more quickly than it increases. For example, decrease at −24 dB/s and increase at +3 dB/s. This allows the VAD to be reactive when a speech frame occurs while the VAD is less reactive during the speech frame itself. In particular, let Pw 0 define a frame noise power floor, and initialize the frame noise power estimate by pw(0)=Pw 0. Then for the first few frames (a learning period) take pw(m)=pr(m); the learning period could be 4 frames. Thereafter the noise power estimate adapts to the current frame power estimate, pr(m):
Lastly, when the ratio of the current frame power estimate to the current frame noise power estimate exceeds a threshold, the VAD outputs a decision that the current frame contains speech; otherwise it does not. To increase the VAD decision reliability, another preferred embodiment method provides a three-state decision: "inactive", "marginally active", or "strongly active". In more detail: define decision thresholds τVAD,1 and τVAD,2; then the VAD decision, dVAD(m), that the mth frame is given by:
Practical values for the thresholds could be τVAD,1=4 and τVAD,2=16.
3. Automatic Gain Control
In step (4) the use of two different downward time constants contributes to the fast gain adjustment with minimal output speech distortion. It is necessary to set the initial speech power to a large number in order to avoid excessively amplifying the input signal at the beginning. It makes the gain adjustment faster to use the faster downward time constant until the estimated speech power comes down to the actual frame power level from the high initial level. Then, when the estimated speech power gets to the same level as the frame power, the downward time constant is switched to the slower constant to minimize the output speech distortion.
The use of the VAD decision in steps (5) and (6) makes the AGC robust to the VAD decision error and allows the AGC to use a simple VAD method instead of an accurate VAD requiring higher computational complexity. The VAD decision (the knowledge of whether the input frame is speech or silence) allows the AGC to avoid excessive amplification of a silence frame. However, the VAD decision error could cause the AGC to adjust the scaling factor in the wrong way for the speech or silence frame. In the preferred embodiment AGC, even if the VAD classifies a silence frame as containing speech activity by mistake, the slow downward constant in step (5) does not allow the estimated speech power to go down too quickly (i.e., not allow the scaling factor to go up too quickly), and this avoids excessive amplification of the silence frame. On the other hand, even if the VAD classifies a frame containing speech as a silence frame by mistake, the estimated speech power is still allowed to move upward with the fast time constant instead of remaining unchanged as described in step (6). This allows the AGC to adjust the scaling factor to an appropriate level in the speech onset and to avoid peak clipping of the signal.
4. Echo Cancellation
A first preferred embodiment echo canceller, as could be part of the system of
The LMS method adaptively updates the time-dependent filter ĥn(k) from the current error signal, the corresponding prior far-end speech samples, and an adaptation parameter. In particular, adapt by minimizing the expected e(n)2 for random inputs by a steepest-descent method which computes the gradient with respect to the filter components as variables (∂(e(n)2)/∂ĥf(k)=−2e(n)x(n−k)) and updates accordingly:
The block LMS method only updates the acoustic channel estimation filter after each block of L samples of x(n); that is, the L updates are accumulated over the block and then applied:
Typical filter lengths for acoustic channels of a hands-free phone in an automobile would be N=100-300 (e.g., 32 ms reverberation paths at 8 KHz implies 256 filter taps), and acoustic channels in offices or conference rooms would have N roughly five to ten times as large. And taking the block size equal to the filter length is computationally convenient and common. However, some preferred embodiments use a block size such as L=160 (e.g., 20 ms digital speech frame at 8 KHz sampling rate) for synchronizing filter updating with a frame decoding. Further preferred embodiments partition a filter into smaller subfilters to have the subfilter length and block size both comparable to a discrete Fourier transform size; see subsection (d) below.
In N-vector notation the estimated acoustic channel filtering is:
Various methods for controlling the stepsize, μ(n), exist. For example, a correlation between loudspeaker input x(n) and microphone pick up y(n) can be used to control stepsize by presuming a high correlation corresponds to only far-end speech and thus ideally large stepsize for fast adaptation, whereas a small correlation corresponds to both far-end and near-end speech and so adaptation is not feasible and thus a small stepsize.
In contrast, some preferred embodiment update methods compute an optimal stepsize by minimizing the error e(mL+L+j) over its block: j=0, 1, . . . , L−1. In particular, the error signal in block m+1 is:
Now the error signals for a block form an L-vector:
An alternative preferred embodiment uses the updating of the filter to reestimate the echo. That is, optimize the stepsize by minimizing the error using the gradient defined from the initial echo estimate, and then update the filter and reestimate the echo. In particular, for eΔ(mL+L+j) use the gradient defined by eold(mL+L+j) and x(mL+L+j). Thus,
In other words, for frame m+1 the initial estimate for the acoustic channel is ĥmL from frame m; and the initial echo estimate for frame m+1 loudspeaker input x(mL+L+j) is ŷold(mL+L+j)=<ĥ,mL|x(mL+L+j)>. So the initial error estimate is eold(mL+L+j)=y(mL+L+j)−ŷold(mL+L+j). Next, compute the gradient ĥΔ,mL+L from this initial error estimate together with the loudspeaker input. Then compute eΔ(mL+L+j) and the optimal stepsize μopt(mL+L). Lastly, update the filter to ĥmL+L and reestimate the echo as ŷ(mL+L+j)=<ĥmL+L|x(mL+L+j)> and thus reestimate the error as e(mL+L+j)=y(mL+L+j)−ŷ(mL+L+j) which, of course, is equivalent to an update with the already-computed −μopt(mL+L) eΔ(mL+L+j):
Convergence of the adaptive filter is based on the assumption that the only near-end input signal is the echo of the loudspeaker output propagating through the acoustic channel; if there is acoustic noise or the near-end speaker is talking, then the echo cancellation filter can quickly diverge. In a traditional double-talk detector, the energy of the near-end and the far-end signals are compared, and if the near-end energy is too high, then adaptation of the filter is stopped and the filter coefficients are frozen. However, in difficult acoustic echo situations the echo can be so loud as to stop the adaptation, paralyzing the system. In addition, convergence enhancements such as spectral whitening as in forgoing subsection (c) can magnify near-end noise in quiet frequency bands, distorting the estimation process even when the echo appears to be the dominant signal.
To prevent divergence in the presence of near-end signals, some preferred embodiments monitor the amount of filter adaptation per input block and limit the amount of change based on the current echo cancellation state. The filter change is defined by the energy in the filter update normalized by the energy in the current filter; namely, for the mth block define the relative change:
During periods of strong near-end energy, the filter estimate can diverge quickly, which is reflected in large values of ΔmL. Some preferred embodiments limit ΔmL to a maximum value of Δmax by scaling down μ(mL) for blocks where this limit would be exceeded. This ensures that any divergence of the filter will be very slow. In particular, for the update ĥmL+L=ĥmL+μ(mL)ĥΔ,mL (where μ(mL) may be equal to μopt(mL) or may be determine in some other manner) a preferred embodiment replaces μ(mL) with min[μ(mL), √Δmax∥ĥ,mL∥/∥ĥΔmL∥].
Note that the absolute magnitude of the filter change, ∥μ(mL)ĥΔmL∥, can also be controlled as well as this relative magnitude change, but such control requires assumptions about the magnitude of the actual echo response. The limit Δmax can be fixed, for example, at −20 dB, or adaptive as described in subsection (c) below. When combined with a very conservative energy detector to freeze adaptation in obvious near-end speech conditions, this stepsize control provides good protection against divergence of the filter.
(c) Adaptive Control of Stepsize
While control of stepsize provides robustness against divergence of the filter estimate, it can also degrade the ability of the echo canceller to adapt to true changes in the acoustic channel. (The control also extends to the spectral whitening described in the following subsections.) Therefore, preferred embodiment methods adaptively control the relative filter change limit, Δmax (and the spectral whitening noise floor, NF). The control is based on continuously adaptive estimates of two parameters: the current convergence of the acoustic channel estimate (as measured by the maximum echo return loss enhancement, ERLEmax, over recent blocks) and the amount of near-end signal in the current block (echo to near-end noise ratio, ENR). Indeed, define the echo return loss enhancement as ERLE(mL)=10 log10 {∥y(mL)∥2/∥e(mL)∥2}, and track the maximum ERLE with a nonlinear estimator that increases faster than it decreases, providing a measure of currently achievable performance. A preferred embodiment simple example:
First, interpret the near-end input (microphone output) signal, y(n), as a combination of an echo, echo(n) (=h{circle around (�)}x(n)), and noise, v(n). Thus the echo canceller output, e(n), will be the near-end input, y(n), minus the echo estimate, echoest(n) (=ŷ(n)):
Next, let g denote the near-end signal attenuation (echo-return loss enhancement, ERLE) resulting from the current echo canceller for this noisy input block; that is, g2=∥e(mL)∥2/∥y(mL)∥2. Further, define gm as the expected attenuation of the echo only (excluding noise) resulting from the current cancellation (using the echo filter estimate); that is, the current filter misadjustment error:
Approximate gm using ERLEmax because recent blocks with no near-end noise will have attained the maximum ERLE, and ERLEmax only slowly decays. Combining the foregoing equations and solving for the echo-to-noise ratio, ENR:
The preferred embodiment control methods use ERLEmax and ENR to adjust the maximum filter change, Δmax. Thus presume that ERLEmax provides an approximate measure of the echo filter misadjustment error, and that a poor ENR represents a bad input block, dominated by either near-end speech or noise. A reasonable value for the filter relative change limit, Δmax, is the filter misadjustment error because this represents the approximate size of change needed to bring the error to zero. That is, a first simple approximation would be −10 log10 Δmax=ERLEmax. However, good input blocks with high ENR allow greater changes (if needed) and poor blocks with low ENR limit the allowed change even more strictly. Thus other preferred embodiments take −10 log10 Δmax as various ENR-based modifications of this simple approximation. For example,
The foregoing acoustic channel filter block LMS adaptation can be transformed to the frequency domain which decorrelates the input. This permits the stepsize to depend upon frequency and thereby allow for spectral whitening to improve filter convergence. The idea is to use a stepsize in each frequency bin that is inversely proportional to the power spectrum of the far-end speech signal. However, the performance of this method is not reliable; so preferred embodiment frequency-dependent adaptations apply a smoothing (weighted averaging) over frequencies of the power spectrum for use with frequency-dependent stepsize. Block LMS adaptation in the frequency domain has the further benefit of lower computational load because the time-domain convolutions and correlations transform to multiplications in the frequency domain. The following paragraphs provide details.
The discrete Fourier transform is circular (periodic), whereas the desired convolutions-correlations are linear; so implement the transformed adaptation by "overlap-save" or "overlap-add" methods. In particular, first consider an overlap-save implementation with a 2N-point discrete Fourier transform (implemented as an FFT) where, again, N is the acoustic channel estimation filter length; the overlap-save method essentially adds N 0s to the N-length filter so that the wrap-around part of circular convolution contributes 0 and leaves the desired linear part for N of the outputs. Again, presume an adaptation block size, L, of less than or equal to the filter length; subsequent preferred embodiments will partition the filter into subfilters of smaller lengths to allow smaller FFT size which will be comparable with block size.
Let the 2N-vector ĤmL denote the 2N-point FFT of the 2N-vector consisting of the N filter coefficients, ĥmL(0), ĥmL(1), . . . , ĥmL(N−1), plus N 0s; that is, with F denoting the 2N�2N FFT matrix, set:
The L time domain convolutions defining the ŷ(mL+j) transform to multiplications in the diagonal matrix operation X(mL) ĤmL in the frequency domain. Indeed, let Ŷ(mL) denote the 2N-vector resulting from the matrix operation X(mL) ĤmL. The overlap-save method saves the last N components of the 2N-vector F−1Ŷ(mL)=F−1X(mL)ĤmL, which are the desired linear convolutions, and discards the first N components which are circular convolutions. That is, define ŷ(mL) as the N-vector including the desired convolutions:
Once ŷ(mL) is computed (two FFTs, diagonal matrix operation, and IFFT), the L errors for block m may be computed in the time domain: e(mL+j)=y(mL+j)−ŷ(mL+j) for j=0, 1, . . . , L−1; and this is the output of the echo canceller as illustrated in
These error terms form an N-vector, e(mL), which for the case L<N includes 0s in place of e(mL+j) for j=L, L+1, . . . ,N−1. Then, as before, in preparation for another overlap-save frequency-domain computation, augment this vector with N 0s to form a 2N-vector and apply a 2N-point FFT:
Now the updating of the N filter coefficients at the start of the (next) block at time mL+L uses the gradient N-vector ĥΔ,mL which has each component as an L-term correlation of e(mL) and a corresponding part of x(mL); namely, ĥΔ,mL(k)=Σ0≦j≦L−1e(mL+j)x(mL+j−k). The gradient thus appears in the time domain as the first N components of the 2N-vector F−1XH(mL) E(mL); the second N components are discarded as part of the overlap-save method. Then transform the filter adaptation to the frequency domain by augmenting the gradient with 0s in the same manner as for ĥmL:
This updating in the frequency domain allows a generalization of the stepsize to depend upon frequency by simply changing the scalar stepsize into a diagonal matrix multiplying the gradient in the frequency domain:
The preferred embodiment stepsize optimization to find μopt(mL) in subsection (a) can be extended to the spectral whitening stepsize matrix. For example, with μ(mL)kk equal to μ/PmL(k), treat the 1/PmL(k) as part of the gradient, let μ depend upon mL, and then optimize with respect to μ. In particular, compute the analogs of eold(=ŷ−ŷold) and eΔ using the frequency domain; that is, compute a ŷold(mL+L) analog from X(mL+L)ĤmL and an eΔ(mL+L) analog from PmL+L −1X(mL+L)X(mL)HE(mL) where PmL+L −1 is the inverse of the diagonal matrix with matrix elements 1/PmL(k). As before, find the optimal μ as that which minimizes the quadratic error ∥eold(mL+L)−μ(mL)eΔ(mL+L)∥2.
The control of stepsize as in subsections (b) and (c) extend to the spectral whitening stepsize matrix.
The foregoing frequency-domain adaptation can also be implemented using the overlap-add method, sliding DFT, or other methods. Indeed, the block LMS adaptation may be simplified (but degraded) to operate in the frequency domain using circular convolutions (rather than the linear convolutions) and thereby further lower complexity of the computations.
(e) Smoothed Spectral Whitening Stepsize
In contrast to the foregoing frequency domain stepsize, a preferred embodiment frequency-domain stepsize matrix, μ(mL), uses the far-end power spectrum only after smoothing over frequencies. In particular, again let XmL(k) denote the kth component of XmL, the 2N-point FFT of the 2N-vector of far-end samples about mL:
A smoothing filter could be a simple c0=0.5 and c−1=c1=0.25 symmetric filter of length 3. For a block size 160 (20 ms speech frame size) and a filter length of 256, the FFT is 512-point and convenient smoothing filters have lengths up to about 33.
The foregoing preferred embodiment optimal stepsize and stepsize control also apply to the preferred embodiment smoothing of the far-end power spectrum for use in the frequency-dependent stepsize matrix. Further, these preferred embodiments also apply to implementations such as overlap-add, circular convolution, sliding DFT, and other frequency-domain approaches.
(f) Noise Floor for Control of Spectral Whitening
When a modest amount of near-end noise is present, the filter convergence can still be degraded by exaggeration of noise at frequencies where there is little far-end speech excitation. In these cases, the spectral whitening process increases the stepsize in the noise-dominated frequencies; that is, if the far-end smoothed power spectrum, SmL(k), is small for frequency k, then μ(mL)kk=μ/SmL(k) is large. This leads to poor estimates of the filter response. Thus preferred embodiments introduce a noise floor to the spectral whitening. In particular, for the preferred embodiment μ(mL)kk=μ/SmL(k), the modified preferred embodiment is μ(mL)kk=μ/max(NF, SmL(k)) where NF is a noise floor. For a 512-point FFT and 16-bit fixed point samples, the noise floor may have values in the range dB. Analogous other limits are applicable to other μ(mL)kk definitions using the far-end power spectrum.
(g) Adaptive Control of Noise Floor
Again, control of spectral whitening (and stepsize) provides robustness against divergence of the filter estimate, it can also degrade the ability of the echo canceller to adapt to true changes in the acoustic channel. Therefore, preferred embodiment methods adaptively control the spectral whitening noise floor, NF (plus the filter change limit, Δmax). As in the foregoing, the control is based on continuously adaptive estimates of two parameters: the current convergence of the acoustic channel estimate (as measured by the maximum echo return loss enhancement, ERLEmax, over recent blocks) and the amount of near-end signal in the current block (echo to near-end noise ratio, ENR).
The preferred embodiment control methods use ERLEmax and ENR to adjust the noise floor for spectral whitening, NF (plus the maximum filter change, Δmax). In both cases assume that ERLEmax provides an approximate measure of the echo filter misadjustment error, and a poor ENR represents a bad input block, dominated by either near-end speech or noise. For the spectral whitening noise floor, because the filter adaptation is based on the current echo error, set the noise floor, NF, to an estimate of the echo-error-to-noise ratio. The echo error should be the current echo attenuated by ERLEmax, so the echo-error-to-noise ratio is estimated by the ENR attenuated by ERLEmax; that is, a preferred embodiment takes NF=ENR�ERLEmax. Experimentally the appropriate adjustment of the estimation parameters (both Δmax and NF) results in a robust echo canceller that still maintains fast convergence for acoustic channel variations.
(h) Subfilter Energy Proportional Stepsize
A hands-free phone in an automobile has a fairly short acoustic channel and a filter of length 256 together with a block size of 160 may suffice. This permits use of a convenient 512-point FFT. However, more accurate filters or filters for hands-free phones in offices and conference rooms typically require much larger filter length, but the corresponding larger FFTs become unwieldy and the filter adaptation convergence slows. Consequently, preferred embodiments partition the filter into subfilters of convenient length (e.g., 256 taps); and this partitioning allows for each subfilter adaptation to depend upon the subfilter's portion of the total filter strength. Proportional adaptation provides faster initial convergence.
In particular, presume an acoustic channel estimation filter ĥmL of length PN and partition the filter into P subfilters ĥmL (p) with each subfilter of length N by setting: ĥn (p)(k)=ĥn(pN+k). Then the acoustic channel estimation filtering can be written as:
The overall preferred embodiment adaptation in the frequency domain with an energy-proportional scalar stepsize for the subfilters is then
Alternative preferred embodiments account for the phenomenon that the estimation noise in the subfilters with the most energy cannot be reduced below the error in the subfilters with the least energy as the filter coefficients converge; these preferred embodiments limit the larger energies based on the current estimate of the filter measurement noise, so as the filter converges the subfilter stepsizes become evenly distributed. In particular, ρ(p)(mL)=1 when the error becomes small as in the preferred embodiment below.
(i) Stepsize Control for Subfilters
The stepsize control of subsections (b)-(c) and (f)-(g) also applies to the subfilters. In particular, each subfilter has a ΔmL (p) which measures the energy in the subfilter update normalized by the subfilter energy:
Similarly, the noise floors for the subfilters, NF(p), could all be the same, and as a simple example:
The following alternative preferred embodiment has subfilters, frequency-domain computations, optimal stepsize, spectral smoothing, stepsize control, and proportional subfilter stepsizes. Using notation similar to the foregoing, variables persisting from frame m include:
PN (filter length) prior loudspeaker input samples, x(mL+L−j);
P subfilters in frequency domain Ĥ(p) mL;
longterm (autoregressive models) of various powers ∥Ĥ(p) mL∥2, ∥y(mL)∥2, ∥e(mL)∥2, spectra, and ERLEmax(mL).
The method includes the following steps (1) through (18) with noted options.
The preferred embodiments compute the gains (attenuations) for the two amplifiers as a linear combination of the desired attenuation levels for the four states with the linear combination coefficients crudely relating to the probability of the system persisting in the corresponding state. The four coefficients are computed as the relative sizes of four hangover counters; the counters are updated every frame (block) and lie in the range 0 to a maximum, CES,MAX.
The ES system operates roughly as follows; a more detailed description appears in subsequent paragraphs. During a persistent condition (e.g., steady far-end talking and no near-end talking), the ES state (e.g., state (3)) will be constant and at each new frame the counter corresponding to that state (e.g., counter 3) is incremented while the other three counters are decremented with saturation at both 0 and the maximum. This adjusts the gains closer to the desired attenuation levels for such a state. Whereas, at changes in conditions (e.g., a near-end speaker begins talking in addition to the far-end talking which means a transition to double-talk state (2)), the counters need a large adjustment (e.g., counter 2 is incremented to at least a minimum and the other three counters set to 0) in order to approach the desired attenuations. The large counter adjustments may be either quick or with a time-delay which allows for a smoother transition and avoids switching artifacts.
First, denote the Far-end VAD decision as dVAD-DL with DL for "downlink" and the Near-end VAD decision as dVAD-UL with UL for "uplink". Each VAD decision is one of three possibilities, 0 for "inactive", 1 for "marginally active", and 2 for "strongly active". The preferred embodiment ES system may use the preferred embodiment VAD of foregoing section 2 for both the far-end VAD and the near-end VAD, or other VADs may be used provided they have analogous three possible outputs. Similarly, the preferred embodiment ES system may be used with the preferred embodiment acoustic echo canceller of section 4 or any other type of acoustic echo canceller.
The terminal coupling loss (TCL) is essentially the ratio of received input power after attenuation (and applied to the loudspeaker) to acoustic-echo-cancelled input power from the microphone, and thus TCL high indicates far-end talk only, and TCL low indicates near-end talk only, double-talk, or poor echo cancellation. The preferred embodiment TCL Estimator uses smoothed estimates of the signal energies. In particular, let rN and eN denote the observation vectors of the far-end and near-end VADs, respectively. That is, with a sampling interval of length T and sampling time t expressed as integer n when t=t0+nT where to is an initial time, define:
For each input frame (N samples), the ES state is determined in order to update the appropriate counter and thereby determine the gains (attenuations) to be applied in the downlink amplifier (AR) and the uplink amplifier (AS). The ES controller determines the state, updates the corresponding state hangover counter, and computes the gain as follows.
(a) State Determination.
The preferred embodiment ES controller determines the state by the two VAD outputs plus a comparison of the TCL estimate, {hacek over (T)}CL(m), to dynamic thresholds ΓTCL,FE(m), ΓTCL,NE(m) (not dynamic), and ΓTCL,DT(m) for the mth frame; note that the subscripts FE, NE, and DT refer to Far-end, Near-end, and Double-talk, respectively. In particular, first set the dynamic thresholds using the average power, px(m), and reference thresholds, ΓTCL,FE,L, ΓTCL,DT,L, ΓTCL,FE,N, ΓTCL,DT,N, and ΓTCL,NE,0 (where subscript L indicates Loud and subscript N indicates Nominal); plus the power threshold for loud signals in the downlink, ΓLoud:
when 10 log10(px(m))>ΓLoud, set:
when 10 log10(px(m))≦ΓLoud, set:
in both cases
This use of dynamic thresholds allows the ES controller to deal with loud signals in the downlink. Indeed, loud signals in the downlink overdrive the loudspeaker and generate clipping which leads to low acoustic echo cancellation performance in terms of terminal coupling loss with annoying echo residuals in the uplink when in the Far-end only state (3). In-particular, when a loud signal appears in the downlink, decrease the TCL Far-end threshold which favors the Far-end only state (3). A subsequent attenuation is then applied in the uplink.
(b) Counter Update.
To maintain smooth switching in the downlink and uplink attenuations at transitions from one state to another state, preferred embodiments replace immediate switching to the desired attenuations for the current state with a dynamic linear combination of the desired attenuations for the four possible states. As described in following subsection (c), the linear combination coefficients are computed as relative sizes of four "hangover" counters, cES,1(m), cES,2(m), cES,3(m), cES,4(m), where counter cESj(m) corresponds to state j for frame m. Thus updating the counters at each frame adjusts their relative sizes and the attenuations applied by the amplifiers.
In particular, for frame m the counters are updated as follows. First, if there is no state transition (ηES(m)=ηES(m−1)), then increment the counter corresponding to the current state by 1 and decrement the counters of the three other states by 1:
In contrast, when there is a state transition (ηES(m)≠ηES(m−1)), the first preferred embodiments have three possible counter updatings: two with large counter adjustments (quick updating and time delay updating) and the third with the increment/decrement as in the foregoing paragraphs. Thus first check whether any of the criteria for large counter adjustments are met, if not, then increment/decrement. The large adjustment criteria and corresponding counter updatings are:
(i) Quick Updating.
When the state transition is from idle state (1) to a talking state, reset all counters to 0 except the counter for the current state which is incremented:
(ii) Time-delayed counter updating limits other state counters to a "Switching Counter" CES,SW and a "Double-talk Counter" CES,DT, depending upon the "Switching Time" τSW and the "Double-talk Time" τDT, respectively. Both CES,SW and CES,DT depend upon the sampling frequency fe and the frame size, N; namely,
The switching time, τSW, is used for single-talk to single-talk transitions while the double-talk time, τDT, is defined for double-talk to single-talk transitions. The time-delayed updating applies as follows:
when dVAD,DL(m)=2 and max{cES,2(m−1), cES,4(m−1)}>0 update cES,2(m)=min{cES,2(m−1), CES,DT} and cES,4(m)=min{cES,4(m−1), CES,SW}
when dVAD,UL(m)=2 and max{cES,2(m−1), cES,3(m−1)}>0 update cES,2(m)=min{cES,2(m−1), CES,DT+1} and cES,3(m)=min{cES,3(m−1), CES,SW+1}
The first criterion includes a transition from Double-talk state (2) or Near-end state (4) to far-end state (3), and the second criterion includes a transition from Double-talk state (2) or far-end state (3) transition to near-end state (4).
State diagram
(c) Gain (Attenuation) Computation.
Compute the overall downlink and uplink gains (attenuations) gES,DL(m) and gES,UL(m), which are applied in amplifiers AR and AS, respectively, using downlink and uplink "Desired Attenuations" for the four states, aDL,1, aDL,2, aDL,3, aDL,4 and aUL,1, aUL,2, aUL,3, aUL,4, respectively, together with the four counters cESj(m) from the previous subsections as:
To prevent signal discontinuities, the attenuation level is linearly interpolated between the previous and the current frame in the time domain. The first PES samples (typically 16 samples) of the current frame (typically 160 samples) are interpolated to make the transition, thus define the interpolation slopes for the mth frame:
The preferred embodiment desired attenuations, aDLj and aULj, in the tables below provide the following attenuations recommended by the ITU-T Recommendation P.340 "Transmission Characteristics and Speech Quality Parameters of Hands-free Terminals" (May 2000) with Behavior 1 being full-duplex, Behaviors 2a-2c various partial-duplex, and Behavior 3 half-duplex. The right-hand column is for far-end talk only and the other columns for double-talk:
As a simplified (ignoring interpolations) example of the time-delay counter updating, presume a double-talk state (2) has persisted for several frames and thus the counters have saturated: cES,2(m−1)=CES,MAX(=15) and cESj(m−1)=0 for j≠2. The consequent full-duplex attenuations are gES,UL=aUL,2=3 dB (=0.5) and gES,DL=aUL,2=3 dB (=0.5). Now presume the near-end talk disappears for several frames but the far-end talk continues, starting in frame m. Then frame m is the transition from double-talk state (2) to far-end state (3) which has desired attenuations aUL,3=15 dB (=0.032) and aDL,3=0 dB (=1.0). Presuming the far-end talk is strong (i.e., dVAD,DL(m)=2), the counter updating for the transition would be (using CES,DT=CES,SW=5):
The next few frames, m+1, m+2, m+3, . . . , remain in state (3), so there are no state transitions and the increment/decrement counter updates apply. In particular:
Successive frames remaining in far-end talk state (3) continue incrementing the counter cES,3(.) and decrementing the counter cES,2(.) until after 5 frames cES,2(.) has saturated at 0. At this point the attenuations are gES,UL=aUL,3=15 dB and gES,DL=aDL,3=0 dB, the desired attenuations for far-end talk state (3). Note that cES,3(.) continues incrementing until it saturates at CES,MAX=15.
6. Echo Suppression Enhancements
The ES system has preferred embodiments which include one or more additional features: noise floor adjustment (NFA), attenuation level smoothing (ALS), and/or comfort noise generation (CNG). The NFA and the ALS features are computed before the linear gain interpolation while the CNG is applied after.
NFA: The noise floor adjustment avoids excessive attenuation of idle channel noise, the attenuation level in the uplink direction is bounded depending upon the near-end noise level. The NFA uses the signal-to-noise ratio (SNR) estimate in the uplink through the power estimates provided by the uplink VAD:
The noise floor margin, αES(m), is determined with the near-end VAD decision according to the rules:
ALS: Attenuation level smoothing provides smooth gain evolution (i.e., at state transitions) by an exponential averaging method in an iterative form using a forgetting factor, λALS:
CNG: Comfort noise generation is added to the ES output signal to mask excessive attenuation that can introduce noise level fluctuations. Comfort noise is generated by low apss filtering a scaled random noise. The preferred embodiment low pass filter is a second-order infinite impulse response (IIR) filter with a cut-off frequency of fc=1000 Hz; that is, the transfer function is:
The preferred embodiments may be modified while retaining one or more of the features of asymmetrical adaptation of noise and/or speech power estimates, optimal stepsize, spectrally smoothed adaptation, stepsize control, proportional subfilter adaptation, and/or multiple state counters for attenuation combinations.
For example, the various thresholds, limits, and adaptation factors could each have different values; the linear combination of desired attenuations using the counters could be in terms of the attenuations expressed in dB, or nonlinear combinations used; the AGC could saturate the square root of the ratio of the target speech power divided by the estimated speech power to determine the gain, and so forth.
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Miles Santana Clarkson; Jan. 10, 2013Published 12:05pm Tuesday, January 22, 2013
Miles Santana Clarkson was born Jan. 10, 2013 at Crestwood Medical Center to Danielle Caines and Ronald Clarkson II of Harvest.
He weighed seven pounds eight ounces and measured 20 inches.
Grandparents are Monica Caines of Raliegh, N.C.; Althea Brown of Santa Barbara, Calif.; and Ronald Clarkson I of Thailand.
Miles has five siblings, Iyanna Ferguson, 15; Jaelen Jenkins, nine; Jami Clarkson, 16; Brandon Clarkson, 15; and Victoria Clarkson, 13.


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Equipment Financing Means Flexible Solutions For Business Needs
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text: Who turned down the invitation to perform at Kim and Kanye's wedding? Instagram Wed-23-Apr-14 16:00 Share this Tell Us What You Think WTF 0 LOL 0 FAIL 0 OMG 0 HOT 0 CUTE 0 ] By Steph Monks Last year James Franco and Seth Rogan did a parody video of Kanye West's song 'Bound 2'. And surprisingly, Kanye loved it! In fact, he loved it so much, that he asked James Franco and Seth Rogan to do a live performance of it at his and Kim Kardashian's upcoming wedding in Versailles.James Franco says "It would be cool for about 10 seconds, but then there would be Seth with his shirt off in front of all the Kardashians…" You May Also Like Jay-Jay, Mike and Dom re-create Kim K's Paper Mag photoshoot (NSFW) Behind the scenes: JMDBreakTheInternet (NSFW) Kim Kardashian's butt on the cover of Paper Magazine (NSFW) Become a fan of The Edge on Facebook and on Twitter .


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Moby is a multimedia painting, consisting of oil & acrylic paints on a custom cedar canvas.The concept for this piece is focused the story of Moby Dick.
To capture the story in a specific way, I used multiple layers of acrylic and oil paints. This painting was done on raw cedar wood.
The benefits of using raw wood allows the oil from the paints to be absorbed, allowing the painting to dry quicker. This also allowed the paint to seep into the wood, creating more values of color.
You can see more about this piece here... http://www.bleyk.com/moby.html
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Average Fixed Income Analysts in the United States make around $67K per year. In the world of Fixed Income Analysts, overall income ranges from $44K near the bottom to $166K at the top; this can include more than $46K from bonuses and more than $61K from profit sharing in exceptional cases. Experience level and the particular city each impact pay for this group, with the former having the largest influence. The majority of workers are highly satisfied with their job. A large number enjoy medical while a fair number get dental coverage. Vision coverage is also available to more than half. The vast majority of Fixed Income Analysts (82 percent) who took the survey are men. Respondents to the PayScale salary survey provided the data for this report.
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Fixed Income Analysts who responded to the survey report just a handful of professional skills. Those who have experience with Financial Analysis, Microsoft Excel, and Financial Modeling can expect to be compensated well for these skills. Financial Modeling and Microsoft Excel as skills, however, tend to be associated with significantly smaller paychecks.
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Art History students might also be interested in pairing their major with a Museum Studies minor. The baccalaureate minor in Museum Studies provides students with a solid introduction to the museum field, to different aspects of the museum profession, and to the study of artifacts of aesthetic or historic significance.
The Department of Art also offers a unique program for Art History and Studio Art majors. The Albritton Art Institute focuses on 19th and 20th century European and American artists. The program provides fully funded field studies once a semester in order that students might observe and analyze artwork firsthand. Past destinations have included New York City, Vienna, Venice and Chicago.
The Martin Museum of Art is located inside the art building. In addition to its permanent collection, the Martin hosts gallery talks and showcases guest artists, along with annual student and studio art faculty exhibitions.
Though not specific to Art History, Baylor has a variety of study abroad programs that offer transferable credits for Art History majors. Baylor's Art History graduates have gone on to pursue graduate degrees in Art History, while others gain employment in museums, art galleries, auction houses or arts organizations.
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There has been a conversation going on in the Jamie Garcia MRI thread regarding the validity of pitcher WAR. Most of this was posted over there, but I felt it probably deserved its own thread so that more people would see it and follow-up comments could be made without taking that one further off-topic.
Many of us are inclined toward using FIP when discussing pitcher performance. But poster cincinnati chili correctly pointed out linking WAR to FIP can be tough to swallow when we have a guy's runs allowed so readily available. Run prevention has a lot to do with the pitcher's strikeouts, walks and homers, but it's hardly the whole picture. Pitchers can attack hitters in ways that encourage double plays. They can pick off runners. They can ramp up the velocity a bit or increase their focus. Defense matters too. And all of the things players control aside, there's some degree of plain old timing "luck" -- if that triple had come before fly out to deep RF instead of after, it would have produced a run.
So how do we measure pitcher performance at the level of runs (WAR)? There are two popular methods. Fangraphs has traditionally uses a FIP-based pitching WAR. In part this was because defense was already being accounted for in position player's WAR, so they didn't want to double count. Baseball-Reference, on the other hand, uses a WAR based on actual runs allowed, RA9-WAR.
FIP-WAR plays it on the extreme "safe" side, only crediting the pitcher for what we know he's responsible for and assuming average influences from everything else. RA9 goes to the other extreme of giving the pitcher credit for everything that results in actual runs being allowed, including his team's defense and luck.
The reality of pitcher responsibility lies somewhere in the middle; it's a trade-off either way. Sabermetrics-guru TangoTiger's rule of thumb is to take the average of the FIP-WAR and RA-WAR. But recently, Fangraphs rolled out some a few stats to help us better navigate this middle ground. Instead of just having their FIP-WAR, they added RA9-WAR and they added stats that use BABIP and LOB% to help explain the difference between the FIP and RA9 WAR totals.
The conceptual framework: RA9-WAR = FIP-WAR + BIP-Wins + LOB-Wins.
FIP-WAR: Pitcher WAR using FIP-projected runs allowed
RA9-WAR: Pitcher WAR using actual runs allowed
BIP-Wins: The difference between RA9-WAR & FIP-WAR explained by BABIP.
LOB-Wins: The difference between RA9-WAR & FIP-WAR explained by LOB%.
They also show FDP-Wins, which is just the two new pieces added together (the difference between RA9-WAR and FIP-WAR, if you prefer).
Let's take Johnny Cueto as an example, who has a been poster boy for this issue around here:
For his career, he's put up 12.8 WAR using FIP. But using RA9, he's put up 18.4. That's an entire win per season! The new stats help us understand that the difference between his FIP & RA9 can be explained by equal parts BABIP "luck" and LOB% "luck". Interestingly though, some years it's been more one than the other.Code:Season Team RA9-WAR BIP-Wins LOB-Wins FDP-Wins WAR 2008 Reds 1.1 -0.1 0.0 -0.1 1.2 2009 Reds 1.7 0.2 0.3 0.4 1.3 2010 Reds 3.6 0.2 0.8 1.0 2.6 2011 Reds 4.3 1.8 0.0 1.7 2.6 2012 Reds 6.2 -0.1 1.7 1.6 4.5 2013 Reds 1.6 0.8 0.1 0.9 0.6 Total - - - 18.4 2.8 2.8 5.6 12.8
This is interesting. But it doesn't do anything to answer the question, "which is more right"?
I thought that maybe a closer look at the data would help. I looked at all qualified SPs from 2011 to 2013, 139 pitchers. They all had at least 300 IP, but ranged from 300 to over 700. So that I could compare them fairly, I normalized the stats to "per 200 IP".
(A quick but important aside, we have to keep in mind this is not a representative sample of all pitchers in professional baseball. This is a sample of the best of the best professional baseball has had to offer. So if I say that pitchers can't control their LOB%, I don't mean that your or I would have a 75% LOB% if we stepped on a major league mound. I mean that pitchers are good enough to keep a job as a major league SP don't differ much in their ability to sustain a LOB% above or below league average. This is important because it's where our intuitions are prone to get confused.
On to the data! I first looked at the distribution of BIP-Wins, LOB-Wins, and those two combined as FDP-Wins to get a lay of the land.
Code:Min Max Avg SD BIP-Wins -1.9 2.2 0.1 0.8 LOB-Wins -2.0 1.6 -0.2 0.6 FDP-Wins -2.7 2.6 -0.1 1.0
That's pretty straight forward. My groupings are somewhat arbitrary, so don't read too much in to a particular value; it's the basic shape that matters. As we could infer from the table above, about 80% of the guys are within 1 win on the two components and all but a few outliers are within 2 wins. BIP has a bit more variation than LOB, but they're pretty similar.
BIP-Wins and LOB-Wins are virtually uncorrelated (R-sq of .01). This actually surprised me a bit because I figured that LOB% was largely a function of getting more or less outs than expected, which is was a low BABIP measures. But I guess the timing "luck" tends to trump a few more or less outs overall. I guess that makes sense. What this means in practice is that a guy at the one extreme on BIP or LOB is just as likely to be in the middle of the other distribution as anybody else (The 2.2 BIP-Wins guy probably a close-to-average LOB-Wins guy).. This is why the distribution for the combined FDP-Wins is only a little bit wider than the other two instead of twice as wide.
[B]So, does this tell us conclusively whether not this variation is due to the player or teammates/luck? No. However, a random process will tend produce a normal distribution like we see here. Roll two die and you get a lot more 6s, 7s, and 8s (44%) than 2s and 14s (6%). By contrast, measures of elite talent tends to produce distributions that skew in one direction (among MLB regulars, the average is 2 WAR, but the elite go up to 10). That's a big hint for us. If BABIP & LOB% were mostly skill and had a reliable influence on pitcher effectiveness, we'd expect to see some outliers on the "really" good side and then a bunching up toward the bottom.
But let's assume for a second that these things are skills. What would these data tell us? Even if these variances are all due to skill, no regular MLB SP prevents or allows more than about 3 wins worth of runs per season due to non-FIP skills and no more than about 2 wins worth on either BABIP or LOB alone -- and most guys are pretty average.
In the other thread, this came up in the context of Cardinals SP Joe Kelly. Over the last two seasons as a part-time SP, Kelly has a 3.08 ERA (2.69 last year). But his FIP is a pedestrian 4.00. In his brief major league career, he has put up:
BIP-Wins/200 IP: -0.2
LOB-Wins/200 IP: 2.3
If Shelby Miller is healthy, Kelly is going to be back in the bullpen. The question is, were the Cards to get 3 WAR of run prevention from a 1 WAR starter or are they sending a 3 WAR starter to the bullpen for no good reason?
Let me first say, as I explained with Cueto, I don't think FIP is entirely right. Pitchers can and do sustainably prevent/allow runs in ways not captured by FIP. However, I know that both both defense and "luck" play non-trivial roles in run prevention. So if I'm crediting a pitcher for his contribution to the team or trying to project his future performance
Kelly wasn't in my sample because his IP were too low, but his 2.3 LOB-Wins would have outpaced by the field by far. Only 4 SP in the sample were north of 1.0: Tyler Chatwood (1.6), Kris Medlen (1.4), Ivan Nova (1.1) and Vance Worley (1.1). Not coincidentally, 3 of those 4 guys had among the lowest IP totals in the sample, where there is less time for the "lucky" aspect of things to average out.
On one hand, it's possible that Joe Kelly is the best SP in baseball at stranding base-runners, twice as good as everybody not named Chatwood or Medlen. But it's much more likely that Kelly (and Chatwood, Medlen and copmany) have been quite lucky. That's not an either/or proposition; guys with extreme performances are those that are good AND lucky.
But given what I've seen in the data and what we know about the Cardinals defense, if his FIP stays in the 4.00 range, I'd put good money that his RA9-WAR moving forward is going to much closer to his FIP-WAR than it has been so far.
For the record, I'm somewhat concerned about Cueto's RA9 too, because he's probably been good and lucky. But I'm more optimistic with Cueto than Kelly because he pitches in front of a stellar defense and controls the running game as well as any pitcher in baseball, which leads to more outs than his FIP suggests. Unlike Kelly, Cueto's true production probably is a good bit higher than his FIP-WAR suggests (though still shy of his RA9).
And because I was curious and others might be as well, I looked at a few other correlations.
This tells us a few pretty simple things:Code:R R-Sq FIP-WAR & RA9-WAR 0.80 0.64 FIP-WAR & BIP-Wins 0.12 0.01 FIP-WAR & LOB-Wins -0.04 0.00 RA9-WAR & BIP-Wins 0.55 0.31 RA9-WAR & LOB-Wins 0.33 0.11
1. FIP explains about 2/3 of RA-9. BABIP & LOB can explain a lot of the rest, with BIP having a bigger role.
2. FIP is basically not correlated to BIP or LOB. If those things are skills, they are unrelated to do with whatever ability a pitcher has to strike guys out, not walk them, and keep the ball in the yard.
If you want to come up with your own adjusted "ERA" that sits somewhere between FIP and RA9, I'd suggest taking TangoTiger's advice: split the difference. And if you're particularly suspicious of the guy's BABIP and/or LOB, split the difference with FIP again.


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Figure 7.
The first Y/F/WxC-motif in the rust effector candidates is evenly distributed across the N-terminal of the proteins. The cumulative number of the YxC, WxC and FxC versions of the Y/F/WxC-motif plotted according to the position of the first amino acid of the motif, relative to the signal peptide cleavage site in the 178 Pgt (A) and 57 Pt (B) effector candidates. Only the first Y/F/WxC-motif in each protein is included.
Godfrey et al. BMC Genomics 2010 11:317 doi:10.1186/1471-2164-11-317


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The Ariat® All-Around III Children's Half Chap is ideal for schooling in comfortable suede. Sized just right for kids, this half chap has a stretch system over the instep and an accordion stretch panel for function and fit. A highly breathable and moisture-wicking lining keeps the young rider comfortable and dry. Vislon® zipper closes from top down.
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When will Digital Death go mainstream in Israel?
We don't like to think about bereavement - but with so much of our lives stored digitally it's our responsibility to consider what will happen to our personal data when we're no longer around.
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You may not relish thinking about you or your family suffering from injuries or illnesses in the future, yet you have an insurance covering these very options, right?
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