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Exploration Of Alternative Algorithms For Multi Channel Acoustic Echo Cancellation
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Book Synopsis Exploration of Alternative Algorithms for Multi-channel Acoustic Echo Cancellation by : Julian A. Chacon-Castaño
Download or read book Exploration of Alternative Algorithms for Multi-channel Acoustic Echo Cancellation written by Julian A. Chacon-Castaño and published by . This book was released on 2020 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-Channel Acoustic Echo cancellation (MCAEC) is a vital component of delivering clean speech to a virtual personal assistant through a smart speaker with multi-channel audio (stereophonic, etc). The use of the Kalman filter as an alternative adaptive filter methodology for this MCAEC application is explored in this work. The Normalized Least Mean Squares filter (NLMS) serves as a benchmark for the Kalman filter. Simulations using room recordings and measured room responses are employed in this exploration. Useful metrics such as the Word Error Rate (WER) and Echo Return Loss Enhancement (ERLE) help to distinguish performance among the two adaptive filter algorithms. For the single channel case, simulations confirm the cancellation and convergence rate advantage of the Kalman filter, in full-band, but the NLMS filter gives similar results in the sub-band domain, as measured by WER and ERLE. In the multi-channel case, both solutions achieve similar steady state cancellation, but the NLMS offers slightly faster convergence rates. In experiments where adaptation was not frozen, the Kalman filter effectively maintains high echo cancellation by tracking input signal statistics. In most cases, the Kalman filter does not present an appropriate alternative for the MCAEC application in this work.
Book Synopsis Advances in Network and Acoustic Echo Cancellation by : J. Benesty
Download or read book Advances in Network and Acoustic Echo Cancellation written by J. Benesty and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together many advanced topics in network and acoustic echo cancellation aimed towards enhancing the echo cancellation performance of next-generation telecommunication systems. The resulting compendium provides a coherent treatment of such topics not found otherwise in journals or other books.
Book Synopsis A Perspective on Stereophonic Acoustic Echo Cancellation by : Jacob Benesty
Download or read book A Perspective on Stereophonic Acoustic Echo Cancellation written by Jacob Benesty and published by Springer Science & Business Media. This book was released on 2011-07-25 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Single-channel hands-free teleconferencing systems are becoming popular. In order to enhance the communication quality of these systems, more and more stereophonic sound devices with two loudspeakers and two microphones are deployed. Because of the coupling between loudspeakers and microphones, there may be strong echoes, which make real-time communication very difficult. The best way we know to cancel these echoes is via a stereo acoustic echo canceller (SAEC), which can be modelled as a two-input/two-output system with real random variables. In this work, the authors recast this problem into a single-input/single-output system with complex random variables thanks to the widely linear model. From this new convenient formulation, they re-derive the most important aspects of a SAEC, including identification of the echo paths with adaptive filters, double-talk detection, and suppression.
Book Synopsis Deep Learning for Acoustic Echo Cancellation and Active Noise Control by : Hao Zhang
Download or read book Deep Learning for Acoustic Echo Cancellation and Active Noise Control written by Hao Zhang and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Acoustic echo cancellation (AEC) and active noise control (ANC) have attracted increasing attention in research and industrial applications over the past few decades. Conventionally, AEC and ANC are addressed using methods that are based on adaptive signal processing with the least mean square algorithm as the foundation. They are linear systems and do not perform satisfactorily in the presence of nonlinear distortions. However, nonlinear distortions are inevitable in applications of AEC and ANC due to the limited quality of electronic devices such as amplifiers and loudspeakers. Considering the capacity of deep learning in modeling complex nonlinear relationships, we propose deep learning approaches to address AEC and ANC problems in this dissertation. Different from traditional signal processing methods, we formulate AEC as deep learning based speech separation. The proposed approach, called deep AEC, suppresses echo and noise by separating the near-end speech from a microphone signal with the accessible far-end signal as additional information. Our study of deep AEC starts with magnitude-domain estimation, and a recurrent neural network with bidirectional long short-term memory (BLSTM) is trained to estimate a spectral magnitude mask (SMM) from the microphone and far-end signals. Later, a convolutional recurrent network (CRN) is utilized for complex spectral mapping and results in better speech quality. In addition, we explore combining deep learning based and traditional AEC algorithms to further improve AEC performance. Although deep AEC produces significant improvements over traditional AEC methods, there exists a tradeoff between echo suppression and near-end speech quality. To address this, we propose a neural cascade architecture to leverage the advantages of magnitude-domain and complex-domain estimation. The proposed cascade architecture consists of two modules. A CRN is employed in the first module for complex spectral mapping. The output is then fed as an additional input to the second module, where a long short-term memory network (LSTM) is utilized for magnitude mask estimation. The entire architecture is trained in an end-to-end manner with the two modules optimized jointly using a single loss function. This cascade architecture enables deep AEC to obtain robust magnitude estimation as well as phase enhancement. Modern communication devices are usually equipped with multiple microphones and loudspeakers. Building on deep learning based AEC in the single-channel setup, we then investigate multi-channel AEC (MCAEC) and propose a deep learning based approach named deep MCAEC. We find that the deep MCAEC approach avoids the intrinsic non-uniqueness problem in traditional MCAEC algorithms. For MCAEC setup with multiple microphones, combining deep MCAEC with supervised beamforming further improves AEC performance. For ANC, we formulate it as a supervised learning problem for the first time and propose a deep learning approach, called deep ANC, to address the nonlinear ANC problem. The main idea is to employ deep learning to encode the optimal control parameters corresponding to different noises and environments. We start with a frequency-domain method and train a CRN to estimate the real and imaginary spectrograms of the canceling signal from the reference signal so that the corresponding anti-noise can eliminate or attenuate the primary noise in the ANC system. Deep ANC is a fixed-parameter ANC approach and large-scale multi-condition training is key to achieving good generalization and robustness against a variety of noises. The proposed approach outperforms traditional ANC methods, exhibits unique advantages, and can be trained to achieve active noise cancellation no matter whether the reference signal is noise or noisy speech. The latter property could dramatically expand the scope of ANC applicability. Processing latency is a critical issue for ANC due to the causality constraint of ANC systems. Deep ANC is a frequency-domain block-based method, which incurs an algorithmic delay determined by the frame size. This delay may violate the causality constraint of ANC systems and is considered as a shortcoming of frequency-domain ANC algorithms. To address this, a time-domain method using a self-attending recurrent neural network is proposed, which allows for implementing deep ANC with smaller frame sizes. Augmented with a delay-compensated training strategy and a revised overlap-add method, the algorithmic latency of deep ANC is reduced substantially without affecting ANC performance much. Finally, we expand the single-channel deep ANC to the multi-channel setup. The resulting approach, called deep MCANC, is developed for active noise control at multiple spatial points (multi-point ANC) and within a spatial zone (generating a quiet zone). In addition, we evaluate the performance of deep MCANC under different setups and examine the impact of factors such as the number of loudspeakers and microphones, and the position of a secondary source, on MCANC performance.
Book Synopsis Adaptive Identification of Acoustic Multichannel Systems Using Sparse Representations by : Karim Helwani
Download or read book Adaptive Identification of Acoustic Multichannel Systems Using Sparse Representations written by Karim Helwani and published by Springer. This book was released on 2014-07-25 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book treats the topic of extending the adaptive filtering theory in the context of massive multichannel systems by taking into account a priori knowledge of the underlying system or signal. The starting point is exploiting the sparseness in acoustic multichannel system in order to solve the non-uniqueness problem with an efficient algorithm for adaptive filtering that does not require any modification of the loudspeaker signals. The book discusses in detail the derivation of general sparse representations of acoustic MIMO systems in signal or system dependent transform domains. Efficient adaptive filtering algorithms in the transform domains are presented and the relation between the signal- and the system-based sparse representations is emphasized. Furthermore, the book presents a novel approach to spatially preprocess the loudspeaker signals in a full-duplex communication system. The idea of the preprocessing is to prevent the echoes from being captured by the microphone array in order to support the AEC system. The preprocessing stage is given as an exemplarily application of a novel unified framework for the synthesis of sound figures. Finally, a multichannel system for the acoustic echo suppression is presented that can be used as a postprocessing stage for removing residual echoes. As first of its kind, it extracts the near-end signal from the microphone signal with a distortionless constraint and without requiring a double-talk detector.
Book Synopsis System Approach to Robust Acoustic Echo Cancellation Through Semi-blind Source Separation Based on Independent Component Analysis by : Ted S. Wada
Download or read book System Approach to Robust Acoustic Echo Cancellation Through Semi-blind Source Separation Based on Independent Component Analysis written by Ted S. Wada and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We live in a dynamic world full of noises and interferences. The conventional acoustic echo cancellation (AEC) framework based on the least mean square (LMS) algorithm by itself lacks the ability to handle many secondary signals that interfere with the adaptive filtering process, e.g., local speech and background noise. In this dissertation, we build a foundation for what we refer to as the system approach to signal enhancement as we focus on the AEC problem. :We first propose the residual echo enhancement (REE) technique that utilizes the error recovery nonlinearity (ERN) to "enhances" the filter estimation error prior to the filter adaptation. The single-channel AEC problem can be viewed as a special case of semi-blind source separation (SBSS) where one of the source signals is partially known, i.e., the far-end microphone signal that generates the near-end acoustic echo. SBSS optimized via independent component analysis (ICA) leads to the system combination of the LMS algorithm with the ERN that allows for continuous and stable adaptation even during double talk. Second, we extend the system perspective to the decorrelation problem for AEC, where we show that the REE procedure can be applied effectively in a multi-channel AEC (MCAEC) setting to indirectly assist the recovery of lost AEC performance due to inter-channel correlation, known generally as the "non-uniqueness" problem. We develop a novel, computationally efficient technique of frequency-domain resampling (FDR) that effectively alleviates the non-uniqueness problem directly while introducing minimal distortion to signal quality and statistics. We also apply the system approach to the multi-delay filter (MDF) that suffers from the inter-block correlation problem. Finally, we generalize the MCAEC problem in the SBSS framework and discuss many issues related to the implementation of an SBSS system. We propose a constrained batch-online implementation of SBSS that stabilizes the convergence behavior even in the worst case scenario of a single far-end talker along with the non-uniqueness condition on the far-end mixing system. :The proposed techniques are developed from a pragmatic standpoint, motivated by real-world problems in acoustic and audio signal processing. Generalization of the orthogonality principle to the system level of an AEC problem allows us to relate AEC to source separation that seeks to maximize the independence, hence implicitly the orthogonality, not only between the error signal and the far-end signal, but rather, among all signals involved. The system approach, for which the REE paradigm is just one realization, enables the encompassing of many traditional signal enhancement techniques in analytically consistent yet practically effective manner for solving the enhancement problem in a very noisy and disruptive acoustic mixing environment.
Book Synopsis Algorithms for Acoustic Echo Cancellation in the Presence of Double Talk by : Timothy J. Creasy
Download or read book Algorithms for Acoustic Echo Cancellation in the Presence of Double Talk written by Timothy J. Creasy and published by . This book was released on 1999 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Acoustic echo cancellation is an attractive way to enhance speech quality and provide a full-duplex communication channel for hands-free telephony. Among the many implementation challenges, the problem of "double talk" is considered one of the toughest. When near-end speech and the acoustic echo of the far-end speech are simultaneously present in the microphone signal, it is very difficult to separate these two components and provide satisfactory echo attenuation. After providing a thorough overview of the application and the major adaptive filtering algorithms used in echo cancellation, this thesis presents an in-depth study of the published techniques for dealing with double talk. We classify these existing approaches according to their underlying methodology, such as signal level comparison, signal correlation, weight progression monitoring, and dual filter architecture. The strengths and weaknesses of a number of representative algorithms are discussed in some detail. We argue that detection of echo path changes yields a more robust echo canceller than direct double talk detection. The major contribution of this thesis is the development of a novel variable step size approach that uses a measure of the correlation between successive gradient estimates to control the system's adaptation rate. Two main algorithms, denoted GC-VSS3 and PC-VSS, are derived by applying this approach to the Least Mean Squares and Affine Projection algorithms, respectively. We demonstrate the superior performance of the proposed algorithms in a double talk environment. This is done through a series of simulation experiments using white noise, coloured noise, and recorded speech as the input signals. We also show how an auxiliary double talk detector, based on the proposed variable step size technique, may be employed to control the peripheral echo suppression components that are usually required in a hands-free telephone set. Finally, computational complexity is analyzed and shown to be reasonable for practical implementation when certain beneficial properties of the adaptive filter structure are exploited.
Book Synopsis Adaptive Algorithms Employing Tap Selection for Single Channel and Stereophonic Acoustic Echo Cancellation by :
Download or read book Adaptive Algorithms Employing Tap Selection for Single Channel and Stereophonic Acoustic Echo Cancellation written by and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Acoustic Echo Cancellation by : Rui Hou
Download or read book Acoustic Echo Cancellation written by Rui Hou and published by . This book was released on 1999 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Adaptive Filtering by : Lino Garcia Morales
Download or read book Adaptive Filtering written by Lino Garcia Morales and published by IntechOpen. This book was released on 2011-09-06 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive filtering is useful in any application where the signals or the modeled system vary over time. The configuration of the system and, in particular, the position where the adaptive processor is placed generate different areas or application fields such as prediction, system identification and modeling, equalization, cancellation of interference, etc., which are very important in many disciplines such as control systems, communications, signal processing, acoustics, voice, sound and image, etc. The book consists of noise and echo cancellation, medical applications, communications systems and others hardly joined by their heterogeneity. Each application is a case study with rigor that shows weakness/strength of the method used, assesses its suitability and suggests new forms and areas of use. The problems are becoming increasingly complex and applications must be adapted to solve them. The adaptive filters have proven to be useful in these environments of multiple input/output, variant-time behaviors, and long and complex transfer functions effectively, but fundamentally they still have to evolve. This book is a demonstration of this and a small illustration of everything that is to come.
Book Synopsis Acoustic Echo Cancellation Algorithms with TAP Selection for Non-stationary Environments by : Warren Sherliker
Download or read book Acoustic Echo Cancellation Algorithms with TAP Selection for Non-stationary Environments written by Warren Sherliker and published by . This book was released on 2000 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Acoustic Echo and Noise Control by : Eberhard Hänsler
Download or read book Acoustic Echo and Noise Control written by Eberhard Hänsler and published by John Wiley & Sons. This book was released on 2005-02-04 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: Authors are well known and highly recognized by the "acoustic echo and noise community." Presents a detailed description of practical methods to control echo and noise Develops a statistical theory for optimal control parameters and presents practical estimation and approximation methods
Book Synopsis Advanced Signal Processing and Digital Noise Reduction by : Saeed V. Vaseghi
Download or read book Advanced Signal Processing and Digital Noise Reduction written by Saeed V. Vaseghi and published by Vieweg+Teubner Verlag. This book was released on 1996-05 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Estimation and classification. Hidden markov models. Wiener filters. Kalman and adaptive least squared error filters.
Book Synopsis Topics in Acoustic Echo and Noise Control by : Eberhard Hänsler
Download or read book Topics in Acoustic Echo and Noise Control written by Eberhard Hänsler and published by Springer Science & Business Media. This book was released on 2006-08-26 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book treats important topics in "Acoustic Echo and Noise Control" and reports the latest developments. Methods for enhancing the quality of transmitted speech signals are gaining growing attention in universities and in industrial development laboratories. This book, written by an international team of highly qualified experts, concentrates on the modern and advanced methods.
Book Synopsis Audio Signal Processing for Next-Generation Multimedia Communication Systems by : Yiteng (Arden) Huang
Download or read book Audio Signal Processing for Next-Generation Multimedia Communication Systems written by Yiteng (Arden) Huang and published by Springer Science & Business Media. This book was released on 2004-03-31 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Audio Signal Processing for Next-Generation Multimedia Communication Systems presents cutting-edge digital signal processing theory and implementation techniques for problems including speech acquisition and enhancement using microphone arrays, new adaptive filtering algorithms, multichannel acoustic echo cancellation, sound source tracking and separation, audio coding, and realistic sound stage reproduction. This book's focus is almost exclusively on the processing, transmission, and presentation of audio and acoustic signals in multimedia communications for telecollaboration where immersive acoustics will play a great role in the near future.
Book Synopsis Speech Dereverberation by : Patrick A. Naylor
Download or read book Speech Dereverberation written by Patrick A. Naylor and published by Springer Science & Business Media. This book was released on 2010-07-27 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Speech Dereverberation gathers together an overview, a mathematical formulation of the problem and the state-of-the-art solutions for dereverberation. Speech Dereverberation presents current approaches to the problem of reverberation. It provides a review of topics in room acoustics and also describes performance measures for dereverberation. The algorithms are then explained with mathematical analysis and examples that enable the reader to see the strengths and weaknesses of the various techniques, as well as giving an understanding of the questions still to be addressed. Techniques rooted in speech enhancement are included, in addition to a treatment of multichannel blind acoustic system identification and inversion. The TRINICON framework is shown in the context of dereverberation to be a generalization of the signal processing for a range of analysis and enhancement techniques. Speech Dereverberation is suitable for students at masters and doctoral level, as well as established researchers.
Book Synopsis Springer Handbook of Speech Processing by : Jacob Benesty
Download or read book Springer Handbook of Speech Processing written by Jacob Benesty and published by Springer Science & Business Media. This book was released on 2007-11-28 with total page 1170 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook plays a fundamental role in sustainable progress in speech research and development. With an accessible format and with accompanying DVD-Rom, it targets three categories of readers: graduate students, professors and active researchers in academia, and engineers in industry who need to understand or implement some specific algorithms for their speech-related products. It is a superb source of application-oriented, authoritative and comprehensive information about these technologies, this work combines the established knowledge derived from research in such fast evolving disciplines as Signal Processing and Communications, Acoustics, Computer Science and Linguistics.
