A Delay-Based Double-Talk Detector

An acoustic echo cancellation system is one of the most important breakthrough in the field of adaptive systems. Today acoustic echo cancellers (AEC) are an integral part of full duplex hands-free voice communication. Conventional echo cancellers use a linear model to represent the echo path. However many consumer devices include loud-speakers and power amplifiers that generate non-linear distortions.Non-linearity occurs due to the use of low cost electronic loud speakers, microphones and poorly designed enclosures in an AEC system. Non-linearity causes vibration and harmonic distortion and also degrades the speech quality. Double talk detector (DTD) is a key component of an AEC. A DTD is used to sense when the far end signal is corrupted by the near end speech. The DTD freezes the adaptation of model filter to prevent the divergence of the adaptive filter. Various authors have proposed different algorithms for double talk detection. Some of the most popular algorithms are Geigel algorithm, cross-correlation based DTD, normalized cross correlation based DTD, variable impulse response DTD etc. In this paper several double talk detection algorithms in a non-linear platform of an AEC has been discussed.

Successful adaptive echo cancellation in telecommunications depends on a control device called a double-talk (DT) detector. DT refers to the situation when signals from both ends of an echo cancellation system are simultaneously active. In the presence of a DT condition, the role of a DT detector is to prevent divergence of the adaptive filter in an echo cancellation system. This paper presents a novel double-talk detection (DTD) algorithm using a psychoacoustic auditory model. The model exploits the frequency masking properties of the human auditory system. It performs an analysis of the far-end signal and removes spectral components below a perceptual threshold, to create spectral holes without affecting the perceptual quality of the signal. A DT condition can be detected by monitoring the energy level in the created holes. Simulations with real speech data and comparisons with other DTD algorithms are presented to show the performance of the proposed algorithm.

Echo cancelers commonly employ a doubletalk detector (DTD), which is essential to keep the adaptive filter from diverging in the presence of near-end speech and other disruptive noise. There have been numerous algorithms to detect doubletalk in an acoustic echo canceler (AEC). In those applications, typically, the threshold is chosen only by some heuristic method and the performance evaluation is very subjective. In this study, we develop a way to objectively evaluate DTD algorithms based on the standard statistical methods of detection theory. A receiver operating characteristic (ROC) is derived to characterize DTD performance. Several DTD algorithms are examined and simulated under typical real-world operating conditions using measured room responses and signals taken from a digital speech database. The DTD methods are then evaluated and compared using the ROC metric.

In this paper, a single channel Kalman filtering in the spectral domain is proposed for acoustic echo and noise cancellation (AENC). An augmented extended Kalman filter is used in this work which is suitable for processing general complex-valued nonlinear and nonstationary signals. The near-end speech and background noise are modelled to make the filter robust against double-talk and against noise. In this work, the approach for echo cancellation does not depend on double-talk detector (DTD) to model the echo path, when signals other than the echoed far-end signal are present. The performance evaluations are conducted over the NOIZEUS corpus. The experimental results demonstrate that the ideal Kalman filter (with near-end speech parameters) outperforms other enhancement methods of echo cancellation in terms of subjective and objective measures. The non-ideal Kalman filter (when near-end speech parameters are obtained by an EM algorithm) also shows promising results after the ideal Kalman filter.

Echo cancellers typically employ a doubletalk detection (DTD) algorithm in order to keep the adaptive filter from diverging in the presence of near-end speech signal or other disruptive sounds in the microphone signal. A novel doubletalk detection algorithm based on techniques similar to those used for audio signal watermarking was introduced by the authors. The application of the described DTD algorithm within acoustic echo cancellation system is presented. The comparison of the proposed algorithm with very common, but simple Geigel algorithm and representing current state-of-the-art Normalized Cross-Correlation algorithms is performed. Both objective (ROC) and subjective (listening tests) performance evaluation methods are employed to obtain exhaustive evaluation results in simulated real-world conditions. The evaluation results are presented and their relevance is discussed. An issue of algorithms' computational complexity is emphasized and conclusions are drawn.

In this paper, we introduce a Fast Normalized Least Mean square algorithm (FNLMS) to eliminate the acoustic echo in the presence of double talk signal. When the near-end speech is present the performance of the adaptive filtering is degraded, thus, a double-talk detector (DTD) must be used for controlling the Acoustic Echo Cancellation (AEC). A Normalized cross correlation (NCC) method applied to FNLMS algorithm is proposed in this paper. Experimental results using different input signals and real measured impulse response (audio-conference room), show a fast convergence and detection of double-talk of the proposed algorithm compared with NLMS algorithm.

This paper considers an adaptive echo canceller which can be used in tasks of acoustic or electrical echo cancellation. The solution of these tasks usually requires the usage of the adaptive filters with a large number of weights. This means that a lot of computational resources of hardware or software are required for the echo canceller implementation. The usage of the Fast (computationally efficient) Affine Projection (FAP) adaptive filtering algorithm ensures the adaptive filter functional efficiency and complexity tradeoff in the echo cancellation tasks. The algorithm consists of two groups of calculations: a fast calculation of the adaptive filter error and a fast calculation of the normalizing matrix and its inversion. The second group is based on the usage of some calculations adopted from the sliding window Fast Recursive Least Squares adaptive filtering algorithms. However these calculations are potentially unstable. The given paper presents a simplified stable version of the multichannel FAP algorithm. The simplification is achieved due to the diagonalization of the normalizing matrix that ensures a simple procedure of direct calculation of this matrix and its inversion. If the echo signal is noisy (and that what always happens in our real world) then the original and the simplified FAP algorithms demonstrate about the same performance. The simulation of the two-channel acoustic echo cancellers confirms this statement.

Acoustic Echo Cancellation (AEC) is employed in hands-free communication systems to enhance communication experience. Double-Talk Detection (DTD) plays a vital role in AEC to distinguish the far-end and near-end signals and its failure will cause the system divergence. An efficient new DTD algorithm based on the joint signal energy and cross-correlation estimation techniques is proposed in this paper to reduce the DTD faults. The proposed algorithm can provide fast DTD and enhanced system performance without increasing much more computational complexity over the conventional techniques. Simulation results show the performance improvement achieved by the proposed technique.

An integrated acoustic echo and noise canceler is proposed for hands-free telephony applications. The proposed system includes a computationally efficient double-talk detection (DTD) method and a residual echo cancellation algorithm. The DTD method uses two cross-correlation coefficients and is robust in adverse conditions. In the residual echo cancellation approach, a linear prediction error filter removes the short-term correlation of the residual echo and the resulting whitened residual echo is canceled by a noise-reduction filter. The proposed system was implemented using a general purpose digital signal processor (DSP) with 16-b arithmetic.

Most of the echo cancellers are equipped with a double-talk detector (DTD) in order to control the behavior of the adaptive filter during double-talk situations. In this paper, we propose a class of DTDs based on the Holder inequality. These DTDs are simple to implement, have low computational complexity, and perform well even for low echo-to-noise ratios. As a particular case, it is shown that the well-known Geigel algorithm can be obtained from this approach.

This paper presents a normalized cross-correlation- based doubletalk detector for use in a critically sampled subband acoustic echo canceller. The algorithm is derived from an existing doubletalk detector for fullband echo cancellers. The resulting per-subband doubletalk detectors are allowed to control adaptation independently in each subband. Computational complexity reduction techniques are described, along with a noise estimation scheme to compensate for the effects of background noise in hands-free and vehicular environments. Simulation results with narrowband speech doubletalk signals show that the proposed structure can achieve a higher level of convergence than a global doubletalk decision in the presence of doubletalk. Detection probability results are also presented.

This paper proposes a novel adaptive algorithm for an echo canceler. In this algorithm, the number of operations and memory capacity are equivalent to those of the conventional NLMS algorithm but the convergence speed is twice that using the conventional algorithm. This adaptive algorithm is referred to as subband ES (exponentially weighted stepsize). In the algorithm, the frequency bands of the received input signal and echo signal are divided into multiple subbands, and echo is independently canceled in each subband. Each adaptive filter in each subband has independent coefficients with an independent stepsize. The stepsize is time-independent and its weight is exponentially proportional to the change of the impulse response within the frequency region, such as the expected value of the difference between the waveforms of two impulse responses. As a result, the characteristic of the acoustic echo path in each frequency band is analyzed using the adaptive algorithm to improve the convergence characteristic. Using the results of computer simulation and experimental results obtained via an experimental setup with DSP, it is shown that the convergence speed with respect to input voice signal can be about 4 times faster when using echo cancellation based on the new algorithm than in conventional full-band echo cancellation based on the NLMS algorithm. © 1998 Scripta Technica, Electron Comm Jpn Pt 3, 82(3): 49–57, 1999

Mobile phones used in cars require for safety reasons handset-free operation.This implies that a front-end is used which is able to reduce the ambient noise so that an acceptable intelligiblity is guaranteed for the far-end customer. Furthermore, the acoustic echo transmitted from the loudspeaker to the microphone has to be reduced so that it is not audible.Another aspect has to be taken into account: the system has to be robust, i.e. it has to be operable in a wide range of the signal-to-noise ratio down to 0 dB or less. Furthermore the demand for a-priori knowledge should be as low as possible because acquisition of knowledge induces time delays unacceptable for real-time systems and contradicts a low-cost solution which is required for a mass product.New developments in this paper concern the segmentation of the frequency band into subbands for all relevant components: noise reduction, echo cancellation and double-talk detection. Furthermore new concepts for echo reduction are presented.Key wordsRobustnessnoise reductionecho cancellation

Design and implementation of a hybrid sub-band acoustic echo canceller (AEC)

Acoustic Echo Cancelation is a typical event in today's telecommunication fields. The input speech signal interference caused by acoustic echo is disturbing for both users side and causes a reduction in the quality of the original signal. The adaptive filtering techniques are used to reduce the unwanted echo, and increasing quality of the speech signal. This Paper focus on different Adaptive filters algorithms and characterized by the Normalized Least Mean Square (NLMS) and Variable Step Size Least Mean Square (VSSLMS) and also This Paper actualizes Real Time Acoustic Echo Cancellation on Tms320c6713dsk. The primary modules of this reverberation canceller are a versatile channel framework utilizing Normalized Least Mean Square (NLMS) calculation, a Double-Talk Detector (DTD) and a Non-Linear Processor (NLP). The Setup of NLMS based versatile framework, Modified NLMS with Variable Step Size calculations and Frequency Domain based Fast LMS algorithms are to be actualized on the DSP equipment. This implementation shows fast response, speed, convergence of time and good tracking capability. The calculation of different adaptive algorithms must be analysed utilizing MATLAB.