Double-talk Detection Algorithm Research Articles

An Improved Double-talk Detection Algorithm for Echo Cancellation in Teleconference System

Echo cancellation commonly employs a double-talk detector (DTD), which is essential to keep the adaptive filter from diverging in the presence of near-end speech. An improved double-talk detection algorithm is proposed to promote the performance of the echo cancellation in teleconference system in the presence of speech issued from the near-end speaker (double-talk). Based on the partitioned block frequency domain adaptive filter algorithm (PBFDAF), the advanced double-talk detection method is presented in this paper constructs a joint correlation coefficient variable to judge the communication state and the variable is applied as a smoothing parameter to the error signal and then get the final output signal. Simulation results show that the improved algorithm can effectively detect the current voice state, eliminate the echo signal, and keep the near-end speaker’s voice well. The performance of the echo cancellation algorithm is improved when both echo and near end signals are simultaneously active by the proposed technique.

Integrated acoustic echo and background noise suppression based on stacked deep neural networks

In this paper, a regression-based integrated acoustic echo and background noise suppression algorithm was proposed through the use of a deep neural network (DNN) with a multi-layer deep architecture. Motivated by an idea that DNNs are a superior hierarchical generative model for modeling the complex relationships between input features and desired target features through its multiple nonlinear hidden layers, a stacked DNN is developed in a sequential fashion such that the DNN for noise suppression is followed by the DNN for acoustic echo suppression. This algorithm is compared to a single DNN-based integrated system to simultaneously suppress acoustic echoes and noise. When developing the DNN-based regression technique using our approach, spectral envelop estimation is a crucial point for which log-power spectra (LPS) are used as features in order to determine the gain, which ensured nonlinear mapping from the LPS of the frames contaminated by echoes and noise to the LPS of the echo- and noise-free frames. This leads to the successful reduction of acoustic echoes and background noise without an additional double-talk detection algorithm. Additionally, an augmented feature technique is adopted to use additional knowledge derived from conventional noise and acoustic echo suppression techniques when designing the DNN architecture in our algorithm. The proposed DNN-based integrated system to suppress acoustic echoes and noise was evaluated in terms of objective measures and demonstrated a significant improvement over conventional integrated algorithms.

Wavelet-Based ICA Using Maximum Likelihood Estimation and Information-Theoretic Measure for Acoustic Echo Cancellation During Double Talk Situation

Acoustic echo cancellation (AEC) plays a prominent role in the present-day hands-free communication environment, owing to the usage of adaptive digital filter techniques. In a duplex communication scenario, there is a need for a double talk detection algorithm in the near-end speaker system which disables the update of the adaptive filter coefficients, thus hindering the process of echo cancellation and leading to a partial solution. To completely solve this problem, independent component analysis (ICA) is used to separate the far-end echo from the mixture of the near-end speech and the far-end echo signal. This paper proposes a new adaptive digital filter using maximum likelihood estimation of ICA and minimization of mutual information of ICA techniques for AEC. The advancement to this technique is made by transforming the observation into an adequate representation using wavelet decomposition. The performance of the echo cancellation is measured in terms of the echo return loss enhancement (ERLE). Higher ERLE indicates better echo cancellation. From the simulation results, it is found that the minimization of the mutual information of ICA has a higher value of ERLE than that by maximum likelihood estimation. The efficiency of the system thus increases by minimizing the processing time using wavelet ICA-based adaptive filter over the conventional adaptive filter.

Modified Approach for VSS NLMS Algorithm for Echo Cancellation in Teleconference System

communication or wireless phones have become need of everyone in this technological era of global communication. Wireless phones not only provide voice communication, they can also easily be used for other services. But voice quality is always preferable over other services of cellular networks. This demand of superior voice quality, just as like as wired line, over a wireless network has developed and is known as echo cancellation. The main aim of the acoustic echo cancellation is to remove the echoes present in desired signal and to provide echo free speech to the listeners. In this paper, a new approach for acoustic echo cancellation (1) and double talk detection for a teleconference system in non stationary environmental conditions is proposed. In this approach the impulse response of the loud speaker is assumed to be available and is estimated from the digital low pass filter. This approach is more common in the sense that it is applied to all existing algorithms. Performance evaluation of the proposed algorithm is known by calculating echo return loss enhancement (ERLE). This approach shows better performance for non stationary environment and reduces the complexity of both acoustic echo cancellation and double talk detection algorithms and this can be implemented with the help of MATLAB.

Design and Implementation on a Sub-band based Acoustic Echo Cancellation Approach

This paper describes the design and implementation of a sub-band based acoustic echo cancellation approach, which incorporates the normalized least mean square algorithm and the double talk detection algorithm. According to the simulation, the proposed approach works well in the modest linear noisy environment. Since the proposed approach is implemented in fix-pointed C, it can be easily ported into fixed-point DSPs to cancel acoustic echo in real systems.

Double‐talk detector based on audio watermarking.

The double‐talk detection (DTD) algorithm is a vital part of an acoustic echo cancellation system commonly used in the telecommunication applications. The role of the DTD algorithm is to stop the adaptation process of the adaptive filter used for the estimation of echo path response in the presence of double‐talk condition. The typically used DTD solutions are often a compromise between high efficiency and affordable computational cost. The algorithm introduced by the authors is based on a novel principle related to the so‐called semi‐fragile watermarking, making it possible to achieve satisfactory performance with limited processing burden. A hidden signature is embedded into the arriving far‐end speaker signal just before it is replayed to the near‐end speaker. Consequently, the presence of that signature is detected in the signal recorded by the near‐end speaker microphone. The appropriate choice of the employed watermarking technique causes the signature to become undetectable during the near‐end speaker’s talkspurts, precisely identifying the double‐talk periods. The use of echo‐hiding watermarking method allows fulfilling the algorithm requirements. The results of performed experiments prove the good performance of the proposed DTD solution. [Research funded by the Polish Ministry of Science and Higher Education within Grant No. PBZ‐MNiSW‐02‐II‐2007.]

A low complexity double-talk detector based on the signal envelope

A new algorithm for double-talk detection, intended for use in the acoustic echo canceller for voice communication applications, is proposed. The communication system developed by the authors required the use of a double-talk detection algorithm with low complexity and good accuracy. The authors propose an approach to double-talk detection based on the signal envelopes. For each of three signals: the far-end speech, the microphone signal and the echo estimate, an envelope is detected. Next, using these envelopes, a detection function is determined and compared to the threshold. Additionally, a dynamic threshold is introduced in order to improve the accuracy of the algorithm. The results of the simulations presented in the paper proved that the accuracy of double-talk detection obtained using the proposed algorithm is higher than in the Geigel algorithm and comparable to the correlation-based methods, while the computational complexity of the proposed method remains at an acceptable level. The double-talk detection algorithm presented here may be used in voice communication systems having limited resources, allowing for accurate double-talk detection and, as a consequence, efficient acoustic echo cancellation.

A Study of Doubletalk Detection Performance in the Presence of Acoustic Echo Path Changes

An efficient and well-performing double-talk detection (DTD) algorithm is a vital part of a practically working acoustic echo canceller. However, recent algorithms are typically evaluated using a static time-invariant room acoustic impulse response, omitting a proper treatment of the case when the acoustic path is changing. In this work, we introduce a common framework to objectively evaluate how path changes affect the DTD performance. Via extensive numerical simulations, we conclude that the main factor in acoustic path changes affecting the DTD performance for some of the more common DTD algorithms is variations in the damping of the acoustic path.

Acoustic echo cancellation and doubletalk detection using estimated loudspeaker impulse responses

In this paper, we present a new approach to acoustic echo cancellation and doubletalk detection for a teleconferencing system including a loudspeaker for which an estimate of the loudspeaker impulse response is available. The approach is general in the sense that it may be applied to most existing acoustic echo cancellation and doubletalk detection algorithms. We show that the new approach reduces the computational complexity for both the echo cancellation and the doubletalk detection algorithms. Furthermore, the numerical examples show that the new approach also may increase the echo cancellation and doubletalk detection performances.

Double-talk detection algorithm based on theI 2 norm

Echo canceller generally needs a double-talk detector which is used to keep the adaptive filter from diverging in the appearance of near-end speech. In this paper we adopt a new double-talk detection algorithm based onl 2 norm to detect the existence of near-end speech in an acoustic echo canceller. We analyze this algorithm from the point of view of functional analysis and point out that the proposed double-talk detection algorithm has the same performance as the classic one in a finite Banach space. The remarkable feature of this algorithm is its higher accuracy and better computation complexity. The fine properties of this algorithm are confirmed by computer simulation and the application in a multimedia communication system.

A new double-talk detection algorithm based on the orthogonality theorem

The algorithm not only prevents the echo canceler from being disturbed by double talking but also tracks the echo path variations. Although the algorithm requires more computation and storage than conventional algorithms, excellent double-talk interference protection performance and echo path tracking have been obtained. >