Echo Cancellation : the generalized likelihood ratio test for double-talk vs. channel change

Echo cancellers are required in both electrical (impedance mismatch) and acoustic (speaker-microphone coupling) applications. One of the main design problems is the control logic for adaptation. Basically, the algorithm weights should be frozen in the presence of double-talk and adapt quickly in the absence of double-talk. The optimum likelihood ratio test (LRT) for this problem was studied in a recent paper. The LRT requires a priori knowledge of the background noise and double-talk power levels. Instead, this paper derives a generalized log likelihood ratio test (GLRT) that does not require this knowledge. The probability density function of a sufficient statistic under each hypothesis is obtained and the performance of the test is evaluated as a function of the system parameters. The receiver operating characteristics (ROCs) indicate that it is difficult to correctly decide between double-talk and a channel change, based upon a single look. However, detection based on about 200 successive samples yields a detection probability close to unity (0.99) with a small false alarm probability (0.01) for the theoretical GLRT model. Application of a GLRT-based echo canceller (EC) to real voice data shows comparable performance to that of the LRT-based EC given in a recent paper

Delay Estimator and Improved Proportionate Multi-Delay Adaptive Filtering Algorithm

This paper pertains to speech and acoustic signal processing, and particularly to a determination of echo path delay and operation of echo cancellers. To cancel long echoes, the number of weights in a conventional adaptive filter must be large. The length of the adaptive filter will directly affect both the degree of accuracy and the convergence speed of the adaptation process. We present a new adaptive structure which is capable to deal with multiple dispersive echo paths. An adaptive filter according to the present invention includes means for storing an impulse response in a memory, the impulse response being indicative of the characteristics of a transmission line. It also includes a delay estimator for detecting ranges of samples within the impulse response having relatively large distribution of echo energy. These ranges of samples are being indicative of echoes on the transmission line. An adaptive filter has a plurality of weighted taps, each of the weighted taps having an associated tap weight value. A tap allocation/control circuit establishes the tap weight values in response to said detecting means so that only taps within the regions of relatively large distributions of echo energy are turned on. Thus, the convergence speed and the degree of estimation in the adaptation process can be improved

Normalized Double-Talk Detection Based on Microphone and AEC Error Cross-correlation

In this paper, we present two different double-talk detection schemes for Acoustic Echo Cancellation (AEC). First, we present a novel normalized detection statistic based on the cross-correlation coefficient between the microphone signal and the cancellation error. The decision statistic is designed in such a way that it meets the needs of an optimal double-talk detector. We also show that the proposed detection statistic converges to the recently proposed normalized cross-correlation based double-talk detector, the best known cross-correlation based detector. Next, we present a new hybrid double-talk detection scheme based on a cross-correlation coefficient and two signal detectors. The hybrid algorithm not only detects double-talk but also detects and tracks any echo-path variations efficiently. We compare our results with other cross-correlation based double-talk detectors to show their effectiveness

Simple and efficient solutions to the problems associated with acoustic echo cancellation

This dissertation is a collection of papers that addresses several important problems associated with acoustic/line echo cancellation (AEC/LEC), specifically double-talk and echo-path change detection. A double-talk detector is used to freeze AEC filter\u27s adaptation during periods of near-end speech. This dissertation presents three different novel double-talk detection schemes. Simulations demonstrate the efficiency of the proposed algorithms --Abstract, page iii

A Modified Cross Correlation Double Talk Detector using Variable Threshold for Acoustic Echo Cancellation

The presence of echo in the communication systems reduces the speech quality and can be overcome by using Acoustic Echo Cancellers (AEC). Acoustic Echo Canceller is a special device which estimates the echo and subtracts it from the microphone signal. Adaptive filters are used for this purpose. Adaptive filters diverge when in addition to far end signal, near end signal is also present. This situation is known as double talk which is handled by double talk detectors (DTD). Cross correlation based DTD is an attractive approach in which cross correlation between two signals give decision parameter. This parameter is compared to constant threshold to give decision. The constant threshold based double talk detector increases the probability of missed detection and increases the residual error of echo canceller. Thus degrades the performance of Acoustic echo canceller. In this paper, a new variable threshold based double talk detector is proposed in which a threshold value is evaluated with respect to the power of near end signal and far end signal. The proposed method shows the reduced probability of missed detections and mean square error, hence improving AEC performance. For updating of the filter coefficients, Variable Step Size Least Mean Square algorithm is used

The Visible and Near Infrared module of EChO

The Visible and Near Infrared (VNIR) is one of the modules of EChO, the Exoplanets Characterization Observatory proposed to ESA for an M-class mission. EChO is aimed to observe planets while transiting by their suns. Then the instrument had to be designed to assure a high efficiency over the whole spectral range. In fact, it has to be able to observe stars with an apparent magnitude Mv= 9-12 and to see contrasts of the order of 10-4 - 10-5 necessary to reveal the characteristics of the atmospheres of the exoplanets under investigation. VNIR is a spectrometer in a cross-dispersed configuration, covering the 0.4-2.5 micron spectral range with a resolving power of about 330 and a field of view of 2 arcsec. It is functionally split into two channels respectively working in the 0.4-1 and 1.0-2.5 micron spectral ranges. Such a solution is imposed by the fact the light at short wavelengths has to be shared with the EChO Fine Guiding System (FGS) devoted to the pointing of the stars under observation. The spectrometer makes use of a HgCdTe detector of 512 by 512 pixels, 18 micron pitch and working at a temperature of 45K as the entire VNIR optical bench. The instrument has been interfaced to the telescope optics by two optical fibers, one per channel, to assure an easier coupling and an easier colocation of the instrument inside the EChO optical bench.Comment: 26 page

A Multidelay Double-Talk Detector Combined with the MDF Adaptive Filter

The multidelay block frequency-domain (MDF) adaptive filter is an excellent candidate for both acoustic and network echo cancellation. There is a need for a very good double-talk detector (DTD) to be combined efficiently with the MDF algorithm. Recently, a DTD based on a normalized cross-correlation vector was proposed and it was shown that this DTD performs much better than the Geigel algorithm and other DTDs based on the cross-correlation coefficient. In this paper, we show how to extend the definition of a normalized cross-correlation vector in the frequency domain for the general case where the block size of the Fourier transform is smaller than the length of the adaptive filter. The resulting DTD has an MDF structure, which makes it easy to implement, and a good fit with an echo canceler based on the MDF algorithm. We also analyze resource requirements (computational complexity and memory requirement) and compare the MDF algorithm with the normalized least mean square algorithm (NLMS) from this point of view.</p

A Novel Normalized Cross-Correlation Based Echo-path Change Detector

A double-talk detector is used to freeze acoustic echo canceller\u27s (AEC) filter adaptation during periods of near-end speech. Increased sensitivity towards double-talk results in declaring echo-path changes as double-talk which adversely effects the performance of an AEC as we freeze adaptation when we really need to adapt. Thus, we need an efficient and simple echo-path change detector so as to differentiate any echo-path variations from double-talk condition. In this paper, we derive a novel test statistic for echo-path change detection. The proposed decision statistic detects any echo-path variations, is normalized properly and is computationally very efficient as compared to existing techniques. Simulations demonstrate the efficiency of the proposed algorithm