US20070263881A1 - Method and apparatus for locating a talker - Google Patents
Method and apparatus for locating a talker Download PDFInfo
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- US20070263881A1 US20070263881A1 US11/828,118 US82811807A US2007263881A1 US 20070263881 A1 US20070263881 A1 US 20070263881A1 US 82811807 A US82811807 A US 82811807A US 2007263881 A1 US2007263881 A1 US 2007263881A1
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- localization
- audio signals
- talker
- estimates
- speech activity
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R3/00—Circuits for transducers, loudspeakers or microphones
- H04R3/005—Circuits for transducers, loudspeakers or microphones for combining the signals of two or more microphones
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
- G01S3/80—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using ultrasonic, sonic or infrasonic waves
- G01S3/801—Details
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
- G01S3/80—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using ultrasonic, sonic or infrasonic waves
- G01S3/802—Systems for determining direction or deviation from predetermined direction
- G01S3/805—Systems for determining direction or deviation from predetermined direction using adjustment of real or effective orientation of directivity characteristics of a transducer or transducer system to give a desired condition of signal derived from that transducer or transducer system, e.g. to give a maximum or minimum signal
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
- G10L21/0208—Noise filtering
- G10L21/0216—Noise filtering characterised by the method used for estimating noise
- G10L2021/02161—Number of inputs available containing the signal or the noise to be suppressed
- G10L2021/02166—Microphone arrays; Beamforming
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/78—Detection of presence or absence of voice signals
- G10L2025/783—Detection of presence or absence of voice signals based on threshold decision
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R2201/00—Details of transducers, loudspeakers or microphones covered by H04R1/00 but not provided for in any of its subgroups
- H04R2201/40—Details of arrangements for obtaining desired directional characteristic by combining a number of identical transducers covered by H04R1/40 but not provided for in any of its subgroups
- H04R2201/401—2D or 3D arrays of transducers
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R25/00—Deaf-aid sets, i.e. electro-acoustic or electro-mechanical hearing aids; Electric tinnitus maskers providing an auditory perception
- H04R25/40—Arrangements for obtaining a desired directivity characteristic
- H04R25/407—Circuits for combining signals of a plurality of transducers
Definitions
- the present invention relates generally to audio systems and in particular to a method and apparatus for locating a talker in a noisy or reverberant environment.
- Localization of sources is required in many applications, such as teleconferencing, where the source position is used to steer a high quality microphone beam toward the talker.
- the source position may additionally be used to focus a camera on the talker.
- Localization of acoustic sources is fraught with practical difficulties. Firstly, reflecting walls (or other objects) generate virtual acoustic images of the source, which can be misidentified as real sources by the location estimator algorithm. Secondly, most of the known locator estimator algorithms are unable to distinguish between noise sources and talkers, especially in the presence of correlated noise and during speech pauses. Voice activity detectors have been used to freeze the localization during speech pauses, thereby minimizing the occurrence of incorrect talker localization as a result of echoes or noise.
- spectral conditioning is used to enhance the performance of the estimator algorithm by restricting operation of the estimator to a narrow frequency band chosen to optimize localization rather than acoustic audibility, in contrast with the prior art.
- An activity detector is also used, as known from the prior art, to identify voiced segments.
- a decision logic state machine is implemented for receiving information from the activity detector and spectrally conditioned estimator and in response verifying localization estimates during periods of voice activation.
- the method and apparatus of the present invention result in much faster talker localization than prior art approaches (typically less than 40 milliseconds), and require much less computational power.
- the use of spectral conditioning results in increased resolution (i.e. how close two talkers are allowed to be while ensuring accurate localization).
- the method and apparatus of the present invention are characterized by high operational stability in the presence of noise.
- FIG. 1 is a block diagram of a talker localization system according to the present invention
- FIGS. 2 a, 2 b and 2 c are beampatterns for a five element circular array which is unfiltered ( FIG. 2 a ), filtered to a low frequency band ( FIG. 2 b ), and filtered to a high frequency band ( FIG. 2 c );
- FIG. 3 is a block diagram of a decision logic state machine according to the preferred embodiment of the present invention.
- FIG. 4 is a flowchart showing operation of the state machine in FIG. 3 ;
- FIG. 5 shows the results of a comparison of actual and estimated talker localization using the system of the present invention.
- a talker localization system including an array 100 of microphones, a spectral conditioner 110 , an activity detector 120 , an estimator 130 , decision logic 140 and a steered device 150 . It is believed that while some components of the illustrated embodiment are known in the art (e.g. the estimator 130 and activity detector 120 ), the overall combination of elements is new, as are the addition of spectral conditioner 110 to the estimator 130 , and the specific design of the decision logic 140 , as described in greater detail below.
- the array 100 includes a number of well-known circular microphone arrays, with the microphones covering hundreds of segments of a 360.degree. array. It is common to use five or six microphones per array, although the number of microphones may vary.
- the signals from microphone array 100 are fed to activity detector 120 , spectral conditioner 110 and steered device 150 .
- Activity detector 120 is a module that determines voiced time segments, as discussed in greater detail below. This information is needed in order to freeze the localization during speech pauses. Any kind of voice activity detection or silence detection algorithm may be used (e.g. an adaptive silence detection algorithm).
- Spectral conditioner 110 filters the input to the estimator 130 . Each array channel is filtered separately. The purpose of the filtering is to restrict the estimation procedure to a narrow frequency band, chosen for best performance of the estimator 130 as well as to suppress noise sources. Consequently, the beamformer output is optimized for localization of talkers.
- Estimator 130 generates a first order position estimation, by segment number, as is known from the prior art. However, as discussed above, the output of estimator 130 can become corrupted by reflecting objects, and noise sources. Activity detector 120 and decision logic 140 operate to reduce the impact of such sources, as discussed in greater detail below.
- Decision logic 140 filters the position estimates provided by the estimator 130 .
- the position estimates calculated during speech pauses, are disregarded.
- the remainder of the position estimates are subjected to a verification process.
- the output of the decision logic 140 is a verified final position estimate, which is then used by the steered device 150 .
- Steered Device 150 can be a beamformer, an image tracking algorithm, or other system.
- spectral conditioner 110 it is important to recognize that every array 100 is characterized by a predetermined resolution, which depends on the array size, array geometry, the number of sensors (microphones) used, the sampling frequency, and the frequency band of the source. Except for the frequency band of the source, all of these variables are constants for the purpose of the position estimation algorithm of estimator 130 . Having regard to the resolution, the algorithm can be restricted to look for the source in a finite number of positions/areas (i.e. segments of a circle).
- a beamformer instance is “pointed” at each of the positions (i.e. different attenuation weightings are applied to the various microphone output signals).
- the position having the highest beamformer output is declared to be the source.
- the beamformer instances are used only for energy calculations.
- the quality of the beamformer output signal is not particularly important. Therefore, the simplest beamforming algorithm (delay & sum beamformer) can be used.
- high quality beamformers e.g. filter & sum beamformer
- Using a simpler beamformer results in fewer computations, fewer instructions, and cheaper DSP chips.
- the resolution also depends on the frequency band of the source.
- the frequency band of speech is between 0 and 20 kHz.
- the frequency response of a beamformer tends to vary over this frequency range.
- FIG. 2 a shows the beampattern of a 5-element circular array 100 .
- the shape of the beam results from the array configuration and the distance between the microphones.
- the array does not obtain a minimum phase difference of .pi., which is needed for signal cancellation, thereby broadening the beam.
- the beampattern is shown for a low frequency band signal (200-500 Hz).
- the beampattern is much wider, with poor attenuation in the back.
- the array obtains phase differences of several .pi., resulting in positive interference in the beamforming calculations, and side lobes in the beampattern.
- the beampattern is shown for a high frequency band signal (1200-1500 Hz). In this case, the beampattern is narrow, but with significant side lobes.
- bandpass filtering is provided by spectral conditioner 110 for narrowing the beampattern over certain frequency bands (a narrower beam means a better resolution), and suppressing all noise sources which do not radiate in the chosen frequency band. This restricts the influence of noise sources (e.g. electric motors which radiate mainly between 50 and 600 Hz.)
- the frequency band where the estimator 130 provides the best results has to be computed empirically.
- the choice of best frequency band is a tradeoff between:
- the bandpass filtering provided by spectral conditioner 110 was centered at 1150 Hz with a bandwidth of 300 Hz. Those of skill in the art will however appreciate that other frequency bands can be used.
- decision logic 140 is a state machine which combines the results of activity detector 120 and estimator 130 .
- the decision logic 140 performs two major tasks. Firstly, the decision logic 140 disregards the estimates of source-position provided by estimator 130 during speech pauses (steps 300 and 320 ). Secondly, the decision logic 140 performs a verification operation on position estimates provided by estimator 130 . Specifically, decision logic 140 waits for the localization algorithm to repeat its estimation a predetermined number of times, n, including up to m ⁇ n mistakes.
- a FIFO stack memory 330 stores past estimates. The size of the stack memory and the minimum number n of correct estimates needed for verification are chosen based on the performance of the activity detector 120 and estimator 130 . Every new estimate which has been declared as voiced by activity detector 120 is pushed into the top of FIFO stack memory 330 .
- a counter 340 counts how many times the latest position estimate has occurred in the past, within the size restriction M of the FIFO stack memory 330 . If the current estimate has occurred more than n times (a constant threshold), the current position estimate is verified (step 350 ) and the estimation output is updated (step 360 ) and stored in a buffer (step 380 ). If the occurrence counter output is less than n (the threshold), the output remains as it was before (step 370 ).
- step 300 During speech pauses no verification is performed (step 300 ), and a value of OxFFFFF(xx) is pushed into the FIFO stack primary 330 instead of the estimate. The output is not changed.
- decision logic 140 is set forth in flowchart format with reference to FIG. 4 .
- n Since the number of correct estimates, n, must be smaller than the size of FIFO stack memory 330 , M, the plot has a diagonal shape.
- a stack size of 32 estimates and a threshold of at least 12 correct estimates in the FIFO stack memory 330 provide optimum performance.
- the stack memory size and threshold of correct estimates can, however, be reduced slightly without significant loss of accuracy. Of course, the stack memory size and threshold can be further reduced with a decrease in accuracy.
- the principles of the invention may be applied to any beamforming application, where a beam needs to be steered, including teleconferencing, hearing aid devices, microphone arrays for speech pick up in cars or other noisy environments, video conferencing, etc. Localization algorithms in the field of image processing can benefit from using this acoustic localization algorithm of this invention.
- the position estimate provided by the present invention may be used to focus a camera on the talker.
- the talker localization system is described as including the spectral conditioner and the decision logic, those of skill in the art will appreciate that the spectral conditioner 110 and decision logic 140 may be used with other components.
- the spectral conditioner 110 may be used in conjunction with a Kalman filter instead of the decision logic. All such embodiments, modifications and applications are believed to be within the sphere and scope of the invention as defined by the claims appended hereto.
Abstract
Description
- This application is a divisional of U.S. patent application Ser. No. 09/894,539, filed on Jun. 28, 2001, now pending, which claims priority under 35 U.S.C. §119 to United Kingdom Patent No. 0016142.2, filed on Jun. 30, 2000, the contents of which are herein incorporated by reference in their entirety for all purposes.
- The present invention relates generally to audio systems and in particular to a method and apparatus for locating a talker in a noisy or reverberant environment.
- Localization of sources is required in many applications, such as teleconferencing, where the source position is used to steer a high quality microphone beam toward the talker. In video conferencing systems, the source position may additionally be used to focus a camera on the talker.
- It is known in the art to use electronically steerable arrays of sensors in combination with location estimator algorithms to pinpoint the location of a talker in a room. In this regard, high quality and complex beamformers have been used to measure the power at different positions. Estimator algorithms locate the dominant audio source using power information received from the beamformers. Attempts have been made at improving the performance of prior art beamformers by enhancing acoustical audibility using filtering, etc. The foregoing prior art methodologies are described in Speaker localization using a steered Filter and sum Beamformer, N. Strobel, T. Meier, R. Rabenstein, presented at the Erlangen work shop 99, vision, modeling and visualization, Nov. 17-19, 1999, Erlangen, Germany.
- Localization of acoustic sources is fraught with practical difficulties. Firstly, reflecting walls (or other objects) generate virtual acoustic images of the source, which can be misidentified as real sources by the location estimator algorithm. Secondly, most of the known locator estimator algorithms are unable to distinguish between noise sources and talkers, especially in the presence of correlated noise and during speech pauses. Voice activity detectors have been used to freeze the localization during speech pauses, thereby minimizing the occurrence of incorrect talker localization as a result of echoes or noise.
- According to the present invention, spectral conditioning is used to enhance the performance of the estimator algorithm by restricting operation of the estimator to a narrow frequency band chosen to optimize localization rather than acoustic audibility, in contrast with the prior art. An activity detector is also used, as known from the prior art, to identify voiced segments. However, according to an important aspect of the invention, a decision logic state machine is implemented for receiving information from the activity detector and spectrally conditioned estimator and in response verifying localization estimates during periods of voice activation.
- The method and apparatus of the present invention result in much faster talker localization than prior art approaches (typically less than 40 milliseconds), and require much less computational power. The use of spectral conditioning results in increased resolution (i.e. how close two talkers are allowed to be while ensuring accurate localization). Furthermore, the method and apparatus of the present invention are characterized by high operational stability in the presence of noise.
- A preferred embodiment of the present invention will now be described more fully with reference to the accompanying drawings in which:
-
FIG. 1 is a block diagram of a talker localization system according to the present invention; -
FIGS. 2 a, 2 b and 2 c are beampatterns for a five element circular array which is unfiltered (FIG. 2 a), filtered to a low frequency band (FIG. 2 b), and filtered to a high frequency band (FIG. 2 c); -
FIG. 3 is a block diagram of a decision logic state machine according to the preferred embodiment of the present invention; -
FIG. 4 is a flowchart showing operation of the state machine inFIG. 3 ; and -
FIG. 5 shows the results of a comparison of actual and estimated talker localization using the system of the present invention. - With reference to
FIG. 1 , a talker localization system is provided in accordance with the present invention, including anarray 100 of microphones, aspectral conditioner 110, anactivity detector 120, anestimator 130,decision logic 140 and a steereddevice 150. It is believed that while some components of the illustrated embodiment are known in the art (e.g. theestimator 130 and activity detector 120), the overall combination of elements is new, as are the addition ofspectral conditioner 110 to theestimator 130, and the specific design of thedecision logic 140, as described in greater detail below. - The
array 100 includes a number of well-known circular microphone arrays, with the microphones covering hundreds of segments of a 360.degree. array. It is common to use five or six microphones per array, although the number of microphones may vary. The signals frommicrophone array 100 are fed toactivity detector 120,spectral conditioner 110 and steereddevice 150. -
Activity detector 120 is a module that determines voiced time segments, as discussed in greater detail below. This information is needed in order to freeze the localization during speech pauses. Any kind of voice activity detection or silence detection algorithm may be used (e.g. an adaptive silence detection algorithm). -
Spectral conditioner 110 filters the input to theestimator 130. Each array channel is filtered separately. The purpose of the filtering is to restrict the estimation procedure to a narrow frequency band, chosen for best performance of theestimator 130 as well as to suppress noise sources. Consequently, the beamformer output is optimized for localization of talkers. -
Estimator 130 generates a first order position estimation, by segment number, as is known from the prior art. However, as discussed above, the output ofestimator 130 can become corrupted by reflecting objects, and noise sources.Activity detector 120 anddecision logic 140 operate to reduce the impact of such sources, as discussed in greater detail below. -
Decision logic 140 filters the position estimates provided by theestimator 130. The position estimates calculated during speech pauses, are disregarded. The remainder of the position estimates are subjected to a verification process. The output of thedecision logic 140 is a verified final position estimate, which is then used by the steereddevice 150. - Steered
Device 150 can be a beamformer, an image tracking algorithm, or other system. Before discussing the operation ofspectral conditioner 110, it is important to recognize that everyarray 100 is characterized by a predetermined resolution, which depends on the array size, array geometry, the number of sensors (microphones) used, the sampling frequency, and the frequency band of the source. Except for the frequency band of the source, all of these variables are constants for the purpose of the position estimation algorithm ofestimator 130. Having regard to the resolution, the algorithm can be restricted to look for the source in a finite number of positions/areas (i.e. segments of a circle). - During operation of the
estimator 130, a beamformer instance is “pointed” at each of the positions (i.e. different attenuation weightings are applied to the various microphone output signals). The position having the highest beamformer output is declared to be the source. It should be noted that, in this application, the beamformer instances are used only for energy calculations. The quality of the beamformer output signal is not particularly important. Therefore, the simplest beamforming algorithm (delay & sum beamformer) can be used. In most of the teleconferencing implementations, high quality beamformers (e.g. filter & sum beamformer) are used for measuring the power at each position. Using a simpler beamformer results in fewer computations, fewer instructions, and cheaper DSP chips. - As indicated above, the resolution also depends on the frequency band of the source. The frequency band of speech is between 0 and 20 kHz. The frequency response of a beamformer tends to vary over this frequency range.
-
FIG. 2 a shows the beampattern of a 5-elementcircular array 100. The shape of the beam results from the array configuration and the distance between the microphones. For frequencies with a wavelength greater than double the intermicrophone distance (i.e. .lambda.>2 (mic.sub.x−mic.sub.y)), the array does not obtain a minimum phase difference of .pi., which is needed for signal cancellation, thereby broadening the beam. InFIG. 2 b, the beampattern is shown for a low frequency band signal (200-500 Hz). In contrast withFIG. 2 a, the beampattern is much wider, with poor attenuation in the back. For frequencies resulting in wavelengths .lambda.<2 (mic.sub.x−mic.sub.y), the array obtains phase differences of several .pi., resulting in positive interference in the beamforming calculations, and side lobes in the beampattern. InFIG. 2 c, the beampattern is shown for a high frequency band signal (1200-1500 Hz). In this case, the beampattern is narrow, but with significant side lobes. - In order to improve the performance of the
estimator 130, bandpass filtering is provided byspectral conditioner 110 for narrowing the beampattern over certain frequency bands (a narrower beam means a better resolution), and suppressing all noise sources which do not radiate in the chosen frequency band. This restricts the influence of noise sources (e.g. electric motors which radiate mainly between 50 and 600 Hz.) - The frequency band where the
estimator 130 provides the best results has to be computed empirically. The choice of best frequency band is a tradeoff between: - 1. The frequency band where the array provides best beampattern.
- 2. The frequency band where speech provides most of the audio energy.
- 3. The frequency band with the least noise source energy.
- In a preferred embodiment of the present invention, the bandpass filtering provided by
spectral conditioner 110 was centered at 1150 Hz with a bandwidth of 300 Hz. Those of skill in the art will however appreciate that other frequency bands can be used. - As shown in
FIG. 3 ,decision logic 140 is a state machine which combines the results ofactivity detector 120 andestimator 130. Thedecision logic 140 performs two major tasks. Firstly, thedecision logic 140 disregards the estimates of source-position provided byestimator 130 during speech pauses (steps 300 and 320). Secondly, thedecision logic 140 performs a verification operation on position estimates provided byestimator 130. Specifically,decision logic 140 waits for the localization algorithm to repeat its estimation a predetermined number of times, n, including up to m<n mistakes. - A
FIFO stack memory 330 stores past estimates. The size of the stack memory and the minimum number n of correct estimates needed for verification are chosen based on the performance of theactivity detector 120 andestimator 130. Every new estimate which has been declared as voiced byactivity detector 120 is pushed into the top ofFIFO stack memory 330. Acounter 340 counts how many times the latest position estimate has occurred in the past, within the size restriction M of theFIFO stack memory 330. If the current estimate has occurred more than n times (a constant threshold), the current position estimate is verified (step 350) and the estimation output is updated (step 360) and stored in a buffer (step 380). If the occurrence counter output is less than n (the threshold), the output remains as it was before (step 370). - During speech pauses no verification is performed (step 300), and a value of OxFFFFF(xx) is pushed into the FIFO stack primary 330 instead of the estimate. The output is not changed.
- The operation of
decision logic 140 is set forth in flowchart format with reference toFIG. 4 . - In order to determine the optimum values of n and M, the output of the system for different combination of these parameters, was compared with ideal behavior. The results of this comparison are shown in
FIG. 5 . Shaded area A represents the poorest performance, while areas B, C and D represent progressively better performance. - Since the number of correct estimates, n, must be smaller than the size of
FIFO stack memory 330, M, the plot has a diagonal shape. - It has been determined that, for a given
array 100,activity detector 120 algorithm,spectral condition 110 andestimator 130, a stack size of 32 estimates and a threshold of at least 12 correct estimates in theFIFO stack memory 330 provide optimum performance. The stack memory size and threshold of correct estimates can, however, be reduced slightly without significant loss of accuracy. Of course, the stack memory size and threshold can be further reduced with a decrease in accuracy. - Alternatives and variations of the invention are possible. Furthermore, the principles of the invention may be applied to any beamforming application, where a beam needs to be steered, including teleconferencing, hearing aid devices, microphone arrays for speech pick up in cars or other noisy environments, video conferencing, etc. Localization algorithms in the field of image processing can benefit from using this acoustic localization algorithm of this invention. In video conferencing, the position estimate provided by the present invention may be used to focus a camera on the talker. Although the talker localization system is described as including the spectral conditioner and the decision logic, those of skill in the art will appreciate that the
spectral conditioner 110 anddecision logic 140 may be used with other components. For example, thespectral conditioner 110 may be used in conjunction with a Kalman filter instead of the decision logic. All such embodiments, modifications and applications are believed to be within the sphere and scope of the invention as defined by the claims appended hereto. - Having described preferred embodiments of the invention, it is noted that modifications and variations can be made by persons skilled in the art in light of the above teachings. It is therefore to be understood that changes may be made to the particular embodiments of the invention disclosed that are nevertheless still within the scope and the spirit of the invention as defined by the appended claims.
Claims (11)
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US11/828,118 US20070263881A1 (en) | 2000-06-30 | 2007-07-25 | Method and apparatus for locating a talker |
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GB0016142.2 | 2000-06-30 | ||
GB0016142A GB2364121B (en) | 2000-06-30 | 2000-06-30 | Method and apparatus for locating a talker |
US09/894,539 US7251336B2 (en) | 2000-06-30 | 2001-06-28 | Acoustic talker localization |
US11/828,118 US20070263881A1 (en) | 2000-06-30 | 2007-07-25 | Method and apparatus for locating a talker |
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US09/894,539 Division US7251336B2 (en) | 2000-06-30 | 2001-06-28 | Acoustic talker localization |
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US11/828,118 Abandoned US20070263881A1 (en) | 2000-06-30 | 2007-07-25 | Method and apparatus for locating a talker |
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GB2388001A (en) * | 2002-04-26 | 2003-10-29 | Mitel Knowledge Corp | Compensating for beamformer steering delay during handsfree speech recognition |
JP3910898B2 (en) * | 2002-09-17 | 2007-04-25 | 株式会社東芝 | Directivity setting device, directivity setting method, and directivity setting program |
EP2254350A3 (en) * | 2003-03-03 | 2014-07-23 | Phonak AG | Method for manufacturing acoustical devices and for reducing wind disturbances |
GB0324536D0 (en) | 2003-10-21 | 2003-11-26 | Mitel Networks Corp | Detecting acoustic echoes using microphone arrays |
US7826624B2 (en) * | 2004-10-15 | 2010-11-02 | Lifesize Communications, Inc. | Speakerphone self calibration and beam forming |
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Also Published As
Publication number | Publication date |
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GB2364121A (en) | 2002-01-16 |
US20020001389A1 (en) | 2002-01-03 |
CA2352017A1 (en) | 2001-12-30 |
GB0016142D0 (en) | 2000-08-23 |
CA2352017C (en) | 2007-04-03 |
US7251336B2 (en) | 2007-07-31 |
GB2364121B (en) | 2004-11-24 |
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