Classifications

• • G—PHYSICS
  • G10—MUSICAL INSTRUMENTS; ACOUSTICS
  • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
  • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
  • G10K11/18—Methods or devices for transmitting, conducting or directing sound
  • G10K11/26—Sound-focusing or directing, e.g. scanning
  • G10K11/34—Sound-focusing or directing, e.g. scanning using electrical steering of transducer arrays, e.g. beam steering
  • G10K11/341—Circuits therefor
  • G10K11/345—Circuits therefor using energy switching from one active element to another
• • G—PHYSICS
  • G10—MUSICAL INSTRUMENTS; ACOUSTICS
  • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
  • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
  • G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
  • G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
  • G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04M—TELEPHONIC COMMUNICATION
  • H04M9/00—Arrangements for interconnection not involving centralised switching
  • H04M9/08—Two-way loud-speaking telephone systems with means for conditioning the signal, e.g. for suppressing echoes for one or both directions of traffic

Definitions

• the present invention relates to signal processing, and more particularly to the measurement of signal levels and time delays at multiple signal sensors.
• dual microphones can be used in combination with beamforming methods to reduce the effects of background noise and echoes in an automobile.
• information regarding the relative sensitivities of the microphones with respect to different acoustic sources is used, for example, to form a spatial beam toward a particular user and/or to form a spatial notch against another user or a loudspeaker.
• Such an approach requires that dynamic information with respect to microphone sensitivity be quickly and accurately obtained.
• Figure 1 depicts a prior art system 100 for measuring the relative sensitivities of dual microphones with respect to different signal sources in the context of hands-free mobile telephony.
• the prior art system 100 includes a first microphone 115, a second microphone 125, an adaptive filter 135 and a summing device 140.
• An output y ⁇ (k) of the first microphone 115 is coupled to a positive input of the summing device 140, and an output y 2 (k) of the second microphone 125 is coupled to an input of the adaptive filter 135.
• An output y ⁇ (k) of the adaptive filter 135 is coupled to a negative input of the summing device 140, and an output e(k) of the summing device 140 is used as a feedback signal to the adaptive filter 135.
• the first microphone 115 is positioned nearer a first source 110
• the second microphone 125 is positioned nearer a second source 120.
• the first microphone 115 can be a hands-free microphone attached to a sun visor situated nearer a driver of an automobile
• the second microphone 125 can be a built-in microphone within a mobile unit attached nearer a passenger in the automobile.
• analog pre-processing and analog-to-digital conversion circuitry can be included at the output of each of the first and second microphones 115, 125 so that digital signals are processed by the adaptive filter 135 and the summing device 140.
• the output e(k) of the summing device 140 represents the difference between the output y,(&) of the first microphone 115 and the output y (k) of the adaptive filter 135 and is referred to herein as an error signal.
• filter coefficients of the adaptive filter 135 are adjusted using a least-squares algorithm such that the error signal e(k) is minimized.
• the adaptive filter 135 is adjusted such that the output y ⁇ (k) of the adaptive filter 135 is as close as possible to (i.e. , is an estimator of) the output y ⁇ (k) of the first microphone 115.
• the adaptive filter 135 attempts to model the signal effects created by the physical separation of the microphones 115, 125.
• the adaptive filter 135 is adjusted to provide similar delay and attenuation effects.
• the relative time delay and signal attenuation at the microphones with respect to each user can be calculated based on the coefficients of the adaptive filter 135 as described, for example, in Y.T. Chan, J.M. Riley and J.B. Plant, "A parameter estimation approach to time delay estimation and signal detection", IEEE Transactions on Acoustics, Speech and Signal Processing, vol. ASSP-28, Feb. 1980, which is incorporated herein in its entirety by reference.
• One disadvantage of the system of Figure 1, however, is that its performance deteriorates significantly in the presence of background noise. As a result, the system of Figure 1 is not useful in most practical applications, where significant background noise (e.g., road and traffic noise) is commonplace.
• background noise e.g., road and traffic noise
• the present invention fulfills the above-described and other needs by providing a system in which a fixed filter and an adaptive filter are used in combination to provide accurate and robust estimates of signal levels and time delays for multiple sensors.
• the fixed filter includes at least one relatively narrow passband which is used to distinguish signal sources of interest from broad-band background noise.
• the fixed filter is coupled to a reference sensor and the adaptive filter is coupled to a secondary sensor.
• An error signal derived from the outputs of the fixed filter and the adaptive filter is used to adjust filter coefficients of the adaptive filter according to a suitable least-squares algorithm.
• the coefficients of the fixed filter and the adaptive filter are used to compute estimates of the time delay and relative level between the two sensors. The estimates can then be used to make decisions regarding sensor selection and beamforming.
• the functionality of the system is supplemented with an activity detector which indicates when no signal of interest is present.
• activity detector In the activity detector, accumulated energy in the adaptive filter is compared with an expected least value derived from the coefficients of the fixed filter. When the accumulated energy is smaller than the expected value, indicating that there is no signal of interest present (i.e., only background noise is present), the time delay and relative level estimates are set to appropriate values to ensure proper operation of the system even during periods where no signals of interest are present.
• more than two signal sensors are employed. In such embodiments, one sensor is treated as a reference sensor and coupled to a fixed filter, while each of the additional sensors is coupled to an adaptive filter.
• an error signal derived from the outputs of the fixed filter and the corresponding adaptive filter is used to update the coefficients of the corresponding adaptive filter.
• the present invention provides a computationally simple yet accurate and robust method for estimating the time delays and relative signal levels at multiple sensors.
• the teachings of the invention are applicable in a wide variety of signal processing contexts.
• the invention may be used for other acoustic applications such as teleconferencing.
• the present invention is applicable in radio communication applications where the signals of interest are radio-frequency transmissions (e.g. , from mobile units and/or base stations in a cellular radio system) and the sensors are radio-frequency-sensitive antenna elements.
• Figure 1 depicts the prior art signal level and delay measurement system described above.
• Figure 2 depicts a signal level and delay measurement system constructed in accordance with the present invention.
• Figure 3 depicts relative signal levels and time delays of two signals detected at dual signal sensors.
• Figure 4 depicts an alternate signal level and delay measurement system constructed in accordance with the present invention.
• Figure 5 depicts magnitude and phase responses of an exemplary signal filter which can be employed in the exemplary systems of Figures 2 and 4.
• Figure 6 depicts exemplary speech and noise signals which are used to demonstrate operation of exemplary embodiments of the present invention.
• Figure 7 depicts signal level and delay estimates generated by an exemplary embodiment of the present invention based on the signals of Figure 6.
• Figure 2 depicts a level and delay measurement system 200 constructed in accordance with the teachings of the present invention.
• the system 200 includes a first sensor 215, a second sensor 225, a fixed FIR filter 230, an adaptive FIR filter 235 and a summing device 240.
• An output y (k) of the first sensor 215 is coupled to an input of the fixed filter 230, and an output y F (k) of the fixed filter 230 is coupled to a positive input of the summing device 240.
• An output y 2 (k) of the second sensor 225 is coupled to an input of the adaptive filter 235 and an output y(k) of the adaptive filter 235 is coupled to a negative input of the summing device 240.
• the first sensor 215 is positioned nearer a first signal source 210
• the second sensor 225 is positioned nearer a second signal source 220.
• the first sensor 215 can be a hands-free microphone attached to a sun visor situated nearer a driver of an automobile
• the second sensor 225 can be a built-in microphone within a mobile unit attached nearer a passenger in the automobile.
• the first and second sensors 215, 225 can be antenna elements positioned nearer first and second radio-frequency signal sources, respectively.
• analog pre-processing and analog-to-digital conversion circuitry can be included at the output of each of the first and second sensors 215, 225 so that digital signals are processed by the fixed filter 230, the adaptive filter 235 and the summing device 240.
• the fixed filter 230 is designed to include at least one relatively narrow pass-band of interest.
• a pass-band can correspond to the 300-600 Hz frequency band in which most of the energy of human speech is concentrated.
• a pass-band can correspond to a bandwidth allocated for radio-frequency transmissions .
• the coefficients of the fixed filter 230 can be adjusted as necessary to compensate for changes in application requirements or environmental conditions.
• the fixed filter 230 can be set to optimize received signal-to-noise ratio for a particular automobile installation.
• the coefficients of the filter 230 can be adjusted dynamically, for example in dependence upon measured signal-to-noise ratio.
• the fixed filter 230 is designed to provide unity gain and zero phase in each passband. Additionally, the noise gain of the fixed filter 230 is minimized in order to ensure maximal stop-band attenuation.
• the prior information provided by the fixed filter 230 i.e., the narrowband nature of the signals output by the fixed filter 230
• filter coefficients of the adaptive filter 235 are adjusted using a suitable least-squares algorithm such that the error signal e(k) is minimized and such that the output y(k) of the adaptive filter 235 is as close as possible to the output y F (k) of the fixed filter 230.
• the relative time delay and signal attenuation at the first and second sensors 215, 225 with respect to each source 210, 220 are calculated based on the coefficients of the adaptive filter 235 and the prior information associated with the fixed filter 230.
• an appropriate digital signal processor can be integrated with the system 200 to perform the least-squares update of the adaptive filter 235 and to compute the time delay and signal level estimates.
• Figure 3 depicts a typical example of source and sensor placement in two dimensions.
• first and second sensors 215, 225 are positioned adjacent two signal sources 210, 220.
• a signal emanating from the first signal source 210 (as indicated by a first dashed arc 315) will impinge upon the first signal sensor 215 before impinging upon the second signal sensor 225.
• the signal received at the second sensor 225 due to the first signal source 210 will be a delayed and attenuated version of the signal received at the first sensor 215 due to the same source 210.
• a signal emanating from the second source 220 (as indicated by a second dashed arc 325) will impinge upon the second sensor 225 before impinging upon the first sensor 215, and the signal received at the first sensor 215 due to the second signal source 220 will be a delayed and attenuated version of the signal received at the second sensor 225 due to the same source 220.
• the spacial separation (and thus the corresponding time delay and level attenuation) of the sensors 215, 225 with respect to the first and second signal sources 210, 220 are indicated in Figure 3 by second and first line segments 320, 310, respectively.
• the second sensor input x 2 (k) is generally a delayed and scaled version of the first sensor input x (k).
• x 2 (k) 1/S-x ⁇ k-D), where the scale factor S is greater than zero and where the delay D may take positive as well as negative values.
• D ⁇ 0 e.g. , for signals emanating from the second signal source 220
• the first input x ⁇ k is a delayed and scaled version of the second input x 2 (k).
• the second input x 2 (k) is denoted the delayed signal for all values of D without loss of generality.
• first and second intermediate signals y ⁇ (k), y 2 (k) x ⁇ k -A) ( 1 )
• Figure 4 illustrates the input signals x (k), x 2 (k) and the intermediate signals y (k), y 2 (k) in the context of a level and delay measurement system.
• the system 400 of Figure 4 is identical to the system 200 of Figure 2 except that a delay block 410 (corresponding to the fixed delay ⁇ described above) is positioned between the first sensor 215 and the fixed filter 230.
• a delay block 410 (corresponding to the fixed delay ⁇ described above) is positioned between the first sensor 215 and the fixed filter 230.
• the coefficients of the fixed filter 230 are stored in a first coefficient vector c 0 and that the time-varying coefficients of the adaptive filter 235 are stored in a second coefficient vector c(k).
• the present invention provides a computationally simple yet accurate method for estimating the delay D and the scale factor S based on the measured sensor inputs x ⁇ k) and x 2 (k).
• the method is robust against background noise so that it may be used successfully, for example, in the above described hands-free mobile telephony context.
• the estimated quantities say D k and $ (where k indicates that sensor inputs up to and including time instant k are used for the calculation of D and S), can be used to improve system performance.
• the estimates D k and S k can be used in combination with well known beamforming techniques to electronically enhance and reduce the sensitivity of the sensors 215, 225 with respect to the first and second sources 210, 220.
• a beam may be formed in the direction of that source to optimize its reception.
• spatial filtering can be employed to diminish the sensitivity of the sensors with respect to that source.
• the system can selectively transmit only the signal detected at a particular sensor when a particular source is active. For example, if one sensor is much more sensitive to the passenger than to the driver (e.g., due to a close physical proximity to the passenger), then it may be desirable to transmit only the signal received at that sensor when only the passenger is speaking.
• the signal y ⁇ k) output by the fixed filter 230 (i.e. , the filtered version of the first intermediate signal y (k)) is given by:
• the vector c(k) contains the time varying filter coefficients of the adaptive filter 235.
• ⁇ is a gain factor (constant or time-varying) in the interval 0 ⁇ ⁇ ⁇ 2, and where
• N-LMS Normalized Least Mean Squares
• RLS Recursive Least Squares
• LMS Least Mean Squares
• each of the above defined quantities can be computed using standard digital signal processing components.
• the coefficients of the adaptive filter 235 converge toward a delayed and scaled version of the coefficients of the fixed filter 230.
• the present invention teaches that by incorporating prior knowledge which distinguishes the source signals from background noise, system performance can be significantly improved. To ensure improved overall performance, the priors should be true in all situations.
• the present invention teaches that such prior information is available when the energy in the source signals of interest is concentrated around one or more center frequencies, while the background noise has a relatively flat and broadband frequency content, or power spectral density.
• the present invention teaches that the fixed FIR filter 230 can be designed as a band-pass filter having one or several pass bands. For example, for speech signals in a mobile hands-free scenario, it is reasonable to assume that the energy of the speech signals is concentrated in the interval 100-250Hz.
• the fundamental frequency of a male speaker is typically around 100Hz
• the fundamental frequency of a female speaker is typically around 250Hz.
• the present invention teaches several possible designs alternatives for the fixed filter 230.
• the fixed filter 230 can be designed to include two pass-bands, the first and second passbands having center frequencies of 100Hz and 250Hz, respectively.
• the fixed filter 230 can be designed to include a single pass-band having a center frequency of 200Hz and spanning a frequency band which includes the fundamental frequency of female speakers as well as the first harmonic frequency of male speakers.
• NG filter noise gain
• the adaptive algorithm used to update the adaptive filter 235 will cause the adaptive filter 235 to converge toward a delayed and scaled replica of the fixed filter 230.
• the coefficients of the adaptive filter 235 will converge as follows: a(k) ⁇ Sc D (20)
• equation (22) can be re-written as follows:
• an estimate D k of the time delay D can be computed as:
• the estimate D k can be computed iteratively in practice. Note that the delay gradient dp(D)/dD follows readily from equation (19).
• the present invention teaches that estimates of the scale factor S and the time delay D can be computed in a straightforward fashion.
• each of the above described computations can be carried out using well known digital signal processing components. Due to the consistent prior information provided by the fixed filter 230, the estimates will be valid even in the presence of background noise.
• the system can be further enhanced by the addition of an activity detector which ensures proper system performance even when all signal sources are inactive.
• an activity detector which ensures proper system performance even when all signal sources are inactive.
• the signals x x (k) and x 2 (k) received at the sensors 215, 225 will comprise uncorrelated noise only.
• the adaptive filter coefficients c(k) will converge toward the null vector, meaning that the scale factor estimate k will tend toward zero while the time delay estimate D k may take any value.
• the estimates S k , D k can be explicitly set to appropriate values when an activity detector senses the absence of signals of interest.
• An exemplary activity detector compares an estimate of the filter noise gain to a predetermined threshold (i.e., an expected noise gain value).
• a predetermined threshold i.e., an expected noise gain value.
• An exemplary system can be implemented using the following pseudocode.
• Scale Factor and Time Delay Estimation Routine Filtering compute output from the fixed FIR filter and the adaptive FIR filter ( denotes the running time index) .
• a simple gain control scheme is used in order to set the gain ⁇ to zero if there is low energy in the inputs .
• the instantaneous energy is compared with a long time average .
• emom(k) sum(ylhat (k: -1 :k-L) .
• N-LMS update Update of the adaptive filter coefficients using the N-LMS algorithm.
• Update of estimates of S and D The scaling estimate is smoothed by a first order recursion, while D is estimated by an iterative gradient method. delta denotes the fixed time delay in channel 1.
• LLC LL*C
• PPD [cos (warr* (1-Dhat+delta) ) ; sin (warr* (1- Dhat+delta) ⁇ ] ;
• Dhat Dhat + mu*DPD' * (LLC - Shat * PPD) ;
• Activity detector If the sum square of estimated filter taps are 20dB below the sum square of the expected filter taps, the gain is forced to unity and the delay estimate towards zero.
• an acoustic scenario is considered in which the sensors are presumed to be microphones and the sources are presumed to be human speakers or loudspeakers transmitting human speech.
• a scenario can arise in the context of hands- free mobile telephony used in an automobile environment.
• the example is restricted to two sensors and two sources, those skilled in the art will appreciate that the approach can be applied using an arbitrary number of sources and sensors.
• a rather severe background noise is typically present (e.g. , from an AC-fan, the car engine, the road, the wind etc.).
• the sensitivities of the microphones in different directions are assumed to be as shown in Table 1. - 21 -
• Additive background noise was modeled as white Gaussian noise.
• the noise signals detected at the first and second sensors 215, 225 are depicted in third and fourth plots 630, 620, respectively, of Figure 6.
• the combined speech and noise signals measured at the first and second sensors 215, 225 are depicted in fifth and sixth plots 650, 660, respectively of Figure 6.
• factor estimate S k is depicted in a second plot 720.
• both plots 710, 720 every 50-th sample is displayed.
• Horizontal dashed lines indicate delays of -3, 0, and 9 samples as well as gains of -lOdB, OdB, and 3dB.
• the system properly provides scale factor and time delay estimates, respectively, of Odb and approximately -3 samples when the driver is speaking and -lOdb and approximately 9 samples when the passenger is speaking.
• the activity detector properly sets the scale factor and time delay estimates, respectively, to Odb and 0 samples during the period when both the driver and the passenger are silent.
• the teachings of the present invention are equally applicable in the context of non-causal filtering.
• the adaptive scheme comprises an adaptive block that can serve as a signal smoother, a backward predictor (D ⁇ 0) and/or a forward predictor (D > 0).
• D ⁇ 0 a backward predictor
• D > 0 a forward predictor
• ⁇ can be set based upon system design considerations. For example, ⁇ can be set to cover "most situations” and not “all possible situations” since the system will provide reasonable results even in rare extreme situations.

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• Engineering & Computer Science (AREA)
• Acoustics & Sound (AREA)
• Multimedia (AREA)
• Physics & Mathematics (AREA)
• Signal Processing (AREA)
• Soundproofing, Sound Blocking, And Sound Damping (AREA)
• Circuit For Audible Band Transducer (AREA)
• Interconnected Communication Systems, Intercoms, And Interphones (AREA)
• Noise Elimination (AREA)
• Testing Or Calibration Of Command Recording Devices (AREA)
• Radar Systems Or Details Thereof (AREA)
• Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
• Filters That Use Time-Delay Elements (AREA)
• Indication And Recording Devices For Special Purposes And Tariff Metering Devices (AREA)

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