System approach to robust acoustic echo cancellation through semi-blind source separation based on independent component analysis

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.PhDCommittee Chair: Biing-Hwang Juang; Committee Member: Brani Vidakovic; Committee Member: David V. Anderson; Committee Member: Jeff S. Shamma; Committee Member: Xiaoli M

ADAPTIVE AND NONLINEAR SIGNAL PROCESSING

1996/1997X Ciclo1967Versione digitalizzata della tesi di dottorato cartacea

주파수 및 시간적 상관관계에 기반한 음향학적 에코 억제 기법

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2016. 8. 김남수.In the past decades, a number of approaches have been dedicated to acoustic echo cancellation and suppression which reduce the negative effects of acoustic echo, namely the acoustic coupling between the loudspeaker and microphone in a room. In particular, the increasing use of full-duplex telecommunication systems has led to the requirement of faster and more reliable acoustic echo cancellation algorithms. The solutions have been based on adaptive filters, but the length of these filters has to be long enough to consider most of the echo signal and linear filtering in these algorithms may be limited to remove the echo signal in various environments. In this thesis, a novel stereophonic acoustic echo suppression (SAES) technique based on spectral and temporal correlations is proposed in the short-time Fourier transform (STFT) domain. Unlike traditional stereophonic acoustic echo cancellation, the proposed algorithm estimates the echo spectra in the STFT domain and uses a Wiener filter to suppress echo without performing any explicit double-talk detection. The proposed approach takes account of interdependencies among components in adjacent time frames and frequency bins, which enables more accurate estimation of the echo signals. Due to the limitations of power amplifiers or loudspeakers, the echo signals captured in the microphones are not in a linear relationship with the far-end signals even when the echo path is perfectly linear. The nonlinear components of the echo cannot be successfully removed by a linear acoustic echo canceller. The remaining echo components in the output of acoustic echo suppression (AES) can be further suppressed by applying residual echo suppression (RES) algorithms. In this thesis, we propose an optimal RES gain estimation based on deep neural network (DNN) exploiting both the far-end and the AES output signals in all frequency bins. A DNN structure is introduced as a regression function representing the complex nonlinear mapping from these signals to the optimal RES gain. Because of the capability of the DNN, the spectro-temporal correlations in the full-band can be considered while finding the nonlinear function. The proposed method does not require any explicit double-talk detectors to deal with single-talk and double-talk situations. One of the well-known approaches for nonlinear acoustic echo cancellation is an adaptive Volterra filtering and various algorithms based on the Volterra filter were proposed to describe the characteristics of nonlinear echo and showed the better performance than the conventional linear filtering. However, the performance might be not satisfied since these algorithms could not consider the full correlation for the nonlinear relationship between the input signal and far-end signal in time-frequency domain. In this thesis, we propose a novel DNN-based approach for nonlinear acoustic echo suppression (NAES), extending the proposed RES algorithm. Instead of estimating the residual gain for suppressing the nonlinear echo components, the proposed algorithm straightforwardly recovers the near-end speech signal through the direct gain estimation obtained from DNN frameworks on the input and far-end signal. For echo aware training, a priori and a posteriori signal-to-echo ratio (SER) are introduced as additional inputs of the DNN for tracking the change of the echo signal. In addition, the multi-task learning (MTL) to the DNN-based NAES is combined to the DNN incorporating echo aware training for robustness. In the proposed system, an additional task of double-talk detection is jointly trained with the primary task of the gain estimation for NAES. The DNN can learn the good representations which can suppress more in single-talk periods and improve the gain estimates in double-talk periods through the MTL framework. Besides, the proposed NAES using echo aware training and MTL with double-talk detection makes the DNN be more robust in various conditions. The proposed techniques show significantly better performance than the conventional AES methods in both single- and double-talk periods. As a pre-processing of various applications such as speech recognition and speech enhancement, these approaches can help to transmit the clean speech and provide an acceptable communication in full-duplex real environments.Chapter 1 Introduction 1 1.1 Background 1 1.2 Scope of thesis 3 Chapter 2 Conventional Approaches for Acoustic Echo Suppression 7 2.1 Single Channel Acoustic Echo Cancellation and Suppression 8 2.1.1 Single Channel Acoustic Echo Cancellation 8 2.1.2 Adaptive Filters for Acoustic Echo Cancellation 10 2.1.3 Acoustic Echo Suppression Based on Spectral Modication 11 2.2 Residual Echo Suppression 13 2.2.1 Spectral Feature-based Nonlinear Residual Echo Suppression 15 2.3 Stereophonic Acoustic Echo Cancellation 17 2.4 Wiener Filtering for Stereophonic Acoustic Echo Suppression 20 Chapter 3 Stereophonic Acoustic Echo Suppression Incorporating Spectro-Temporal Correlations 25 3.1 Introduction 25 3.2 Linear Time-Invariant Systems in the STFT Domain with Crossband Filtering 26 3.3 Enhanced SAES (ESAES) Utilizing Spectro-Temporal Correlations 29 3.3.1 Problem Formulation 31 3.3.2 Estimation of Extended PSD Matrices, Echo Spectra, and Gain Function 34 3.3.3 Complexity of the Proposed ESAES Algorithm 36 3.4 Experimental Results 37 3.5 Summary 41 Chapter 4 Nonlinear Residual Echo Suppression Based on Deep Neural Network 43 4.1 Introduction 43 4.2 A Brief Review on RES 45 4.3 Deep Neural Networks 46 4.4 Nonlinear RES using Deep Neural Network 49 4.5 Experimental Results 52 4.5.1 Combination with Stereophonic Acoustic Echo Suppression 59 4.6 Summary 61 Chapter 5 Enhanced Deep Learning Frameworks for Nonlinear Acoustic Echo Suppression 69 5.1 Introduction 69 5.2 DNN-based Nonlinear Acoustic Echo Suppression using Echo Aware Training 72 5.3 Multi-Task Learning for NAES 75 5.4 Experimental Results 78 5.5 Summary 82 Chapter 6 Conclusions 89 Bibliography 91 요약 101Docto

Study on Reduction of Computational Complexity for Volterra Filters by Using Multi-rate Signal Processing and Its Application to Identification of Loudspeaker Systems

関西大

Beiträge zu breitbandigen Freisprechsystemen und ihrer Evaluation

This work deals with the advancement of wideband hands-free systems (HFS’s) for mono- and stereophonic cases of application. Furthermore, innovative contributions to the corr. field of quality evaluation are made. The proposed HFS approaches are based on frequency-domain adaptive filtering for system identification, making use of Kalman theory and state-space modeling. Functional enhancement modules are developed in this work, which improve one or more of key quality aspects, aiming at not to harm others. In so doing, these modules can be combined in a flexible way, dependent on the needs at hand. The enhanced monophonic HFS is evaluated according to automotive ITU-T recommendations, to prove its customized efficacy. Furthermore, a novel methodology and techn. framework are introduced in this work to improve the prototyping and evaluation process of automotive HF and in-car-communication (ICC) systems. The monophonic HFS in several configurations hereby acts as device under test (DUT) and is thoroughly investigated, which will show the DUT’s satisfying performance, as well as the advantages of the proposed development process. As current methods for the evaluation of HFS’s in dynamic conditions oftentimes still lack flexibility, reproducibility, and accuracy, this work introduces “Car in a Box” (CiaB) as a novel, improved system for this demanding task. It is able to enhance the development process by performing high-resolution system identification of dynamic electro-acoustical systems. The extracted dyn. impulse response trajectories are then applicable to arbitrary input signals in a synthesis operation. A realistic dynamic automotive auralization of a car cabin interior is available for HFS evaluation. It is shown that this system improves evaluation flexibility at guaranteed reproducibility. In addition, the accuracy of evaluation methods can be increased by having access to exact, realistic imp. resp. trajectories acting as a so-called “ground truth” reference. If CiaB is included into an automotive evaluation setup, there is no need for an acoustical car interior prototype to be present at this stage of development. Hency, CiaB may ease the HFS development process. Dynamic acoustic replicas may be provided including an arbitrary number of acoustic car cabin interiors for multiple developers simultaneously. With CiaB, speech enh. system developers therefore have an evaluation environment at hand, which can adequately replace the real environment.Diese Arbeit beschäftigt sich mit der Weiterentwicklung breitbandiger Freisprechsysteme für mono-/stereophone Anwendungsfälle und liefert innovative Beiträge zu deren Qualitätsmessung. Die vorgestellten Verfahren basieren auf im Frequenzbereich adaptierenden Algorithmen zur Systemidentifikation gemäß Kalman-Theorie in einer Zustandsraumdarstellung. Es werden funktionale Erweiterungsmodule dahingehend entwickelt, dass mindestens eine Qualitätsanforderung verbessert wird, ohne andere eklatant zu verletzen. Diese nach Anforderung flexibel kombinierbaren algorithmischen Erweiterungen werden gemäß Empfehlungen der ITU-T (Rec. P.1110/P.1130) in vorwiegend automotiven Testszenarien getestet und somit deren zielgerichtete Wirksamkeit bestätigt. Es wird eine Methodensammlung und ein technisches System zur verbesserten Prototypentwicklung/Evaluation von automotiven Freisprech- und Innenraumkommunikationssystemen vorgestellt und beispielhaft mit dem monophonen Freisprechsystem in diversen Ausbaustufen zur Anwendung gebracht. Daraus entstehende Vorteile im Entwicklungs- und Testprozess von Sprachverbesserungssystem werden dargelegt und messtechnisch verifiziert. Bestehende Messverfahren zum Verhalten von Freisprechsystemen in zeitvarianten Umgebungen zeigten bisher oft nur ein unzureichendes Maß an Flexibilität, Reproduzierbarkeit und Genauigkeit. Daher wird hier das „Car in a Box“-Verfahren (CiaB) entwickelt und vorgestellt, mit dem zeitvariante elektro-akustische Systeme technisch identifiziert werden können. So gewonnene dynamische Impulsantworten können im Labor in einer Syntheseoperation auf beliebige Eingangsignale angewandt werden, um realistische Testsignale unter dyn. Bedingungen zu erzeugen. Bei diesem Vorgehen wird ein hohes Maß an Flexibilität bei garantierter Reproduzierbarkeit erlangt. Es wird gezeigt, dass die Genauigkeit von darauf basierenden Evaluationsverfahren zudem gesteigert werden kann, da mit dem Vorliegen von exakten, realen Impulsantworten zu jedem Zeitpunkt der Messung eine sogenannte „ground truth“ als Referenz zur Verfügung steht. Bei der Einbindung von CiaB in einen Messaufbau für automotive Freisprechsysteme ist es bedeutsam, dass zu diesem Zeitpunkt das eigentliche Fahrzeug nicht mehr benötigt wird. Es wird gezeigt, dass eine dyn. Fahrzeugakustikumgebung, wie sie im Entwicklungsprozess von automotiven Sprachverbesserungsalgorithmen benötigt wird, in beliebiger Anzahl vollständig und mind. gleichwertig durch CiaB ersetzt werden kann

Efficient audio signal processing for embedded systems

We investigated two design strategies that would allow us to efficiently process audio signals on embedded systems such as mobile phones and portable electronics. In the first strategy, we exploit properties of the human auditory system to process audio signals. We designed a sound enhancement algorithm to make piezoelectric loudspeakers sound "richer" and "fuller," using a combination of bass extension and dynamic range compression. We also developed an audio energy reduction algorithm for loudspeaker power management by suppressing signal energy below the masking threshold. In the second strategy, we use low-power analog circuits to process the signal before digitizing it. We designed an analog front-end for sound detection and implemented it on a field programmable analog array (FPAA). The sound classifier front-end can be used in a wide range of applications because programmable floating-gate transistors are employed to store classifier weights. Moreover, we incorporated a feature selection algorithm to simplify the analog front-end. A machine learning algorithm AdaBoost is used to select the most relevant features for a particular sound detection application. We also designed the circuits to implement the AdaBoost-based analog classifier.PhDCommittee Chair: Anderson, David; Committee Member: Hasler, Jennifer; Committee Member: Hunt, William; Committee Member: Lanterman, Aaron; Committee Member: Minch, Bradle

Optimization and improvements in spatial sound reproduction systems through perceptual considerations

[ES] La reproducción de las propiedades espaciales del sonido es una cuestión cada vez más importante en muchas aplicaciones inmersivas emergentes. Ya sea en la reproducción de contenido audiovisual en entornos domésticos o en cines, en sistemas de videoconferencia inmersiva o en sistemas de realidad virtual o aumentada, el sonido espacial es crucial para una sensación de inmersión realista. La audición, más allá de la física del sonido, es un fenómeno perceptual influenciado por procesos cognitivos. El objetivo de esta tesis es contribuir con nuevos métodos y conocimiento a la optimización y simplificación de los sistemas de sonido espacial, desde un enfoque perceptual de la experiencia auditiva. Este trabajo trata en una primera parte algunos aspectos particulares relacionados con la reproducción espacial binaural del sonido, como son la escucha con auriculares y la personalización de la Función de Transferencia Relacionada con la Cabeza (Head Related Transfer Function - HRTF). Se ha realizado un estudio sobre la influencia de los auriculares en la percepción de la impresión espacial y la calidad, con especial atención a los efectos de la ecualización y la consiguiente distorsión no lineal. Con respecto a la individualización de la HRTF se presenta una implementación completa de un sistema de medida de HRTF y se introduce un nuevo método para la medida de HRTF en salas no anecoicas. Además, se han realizado dos experimentos diferentes y complementarios que han dado como resultado dos herramientas que pueden ser utilizadas en procesos de individualización de la HRTF, un modelo paramétrico del módulo de la HRTF y un ajuste por escalado de la Diferencia de Tiempo Interaural (Interaural Time Difference - ITD). En una segunda parte sobre reproducción con altavoces, se han evaluado distintas técnicas como la Síntesis de Campo de Ondas (Wave-Field Synthesis - WFS) o la panoramización por amplitud. Con experimentos perceptuales se han estudiado la capacidad de estos sistemas para producir sensación de distancia y la agudeza espacial con la que podemos percibir las fuentes sonoras si se dividen espectralmente y se reproducen en diferentes posiciones. Las aportaciones de esta investigación pretenden hacer más accesibles estas tecnologías al público en general, dada la demanda de experiencias y dispositivos audiovisuales que proporcionen mayor inmersión.[CA] La reproducció de les propietats espacials del so és una qüestió cada vegada més important en moltes aplicacions immersives emergents. Ja siga en la reproducció de contingut audiovisual en entorns domèstics o en cines, en sistemes de videoconferència immersius o en sistemes de realitat virtual o augmentada, el so espacial és crucial per a una sensació d'immersió realista. L'audició, més enllà de la física del so, és un fenomen perceptual influenciat per processos cognitius. L'objectiu d'aquesta tesi és contribuir a l'optimització i simplificació dels sistemes de so espacial amb nous mètodes i coneixement, des d'un criteri perceptual de l'experiència auditiva. Aquest treball tracta, en una primera part, alguns aspectes particulars relacionats amb la reproducció espacial binaural del so, com són l'audició amb auriculars i la personalització de la Funció de Transferència Relacionada amb el Cap (Head Related Transfer Function - HRTF). S'ha realitzat un estudi relacionat amb la influència dels auriculars en la percepció de la impressió espacial i la qualitat, dedicant especial atenció als efectes de l'equalització i la consegüent distorsió no lineal. Respecte a la individualització de la HRTF, es presenta una implementació completa d'un sistema de mesura de HRTF i s'inclou un nou mètode per a la mesura de HRTF en sales no anecoiques. A mès, s'han realitzat dos experiments diferents i complementaris que han donat com a resultat dues eines que poden ser utilitzades en processos d'individualització de la HRTF, un model paramètric del mòdul de la HRTF i un ajustament per escala de la Diferencià del Temps Interaural (Interaural Time Difference - ITD). En una segona part relacionada amb la reproducció amb altaveus, s'han avaluat distintes tècniques com la Síntesi de Camp d'Ones (Wave-Field Synthesis - WFS) o la panoramització per amplitud. Amb experiments perceptuals, s'ha estudiat la capacitat d'aquests sistemes per a produir una sensació de distància i l'agudesa espacial amb que podem percebre les fonts sonores, si es divideixen espectralment i es reprodueixen en diferents posicions. Les aportacions d'aquesta investigació volen fer més accessibles aquestes tecnologies al públic en general, degut a la demanda d'experiències i dispositius audiovisuals que proporcionen major immersió.[EN] The reproduction of the spatial properties of sound is an increasingly important concern in many emerging immersive applications. Whether it is the reproduction of audiovisual content in home environments or in cinemas, immersive video conferencing systems or virtual or augmented reality systems, spatial sound is crucial for a realistic sense of immersion. Hearing, beyond the physics of sound, is a perceptual phenomenon influenced by cognitive processes. The objective of this thesis is to contribute with new methods and knowledge to the optimization and simplification of spatial sound systems, from a perceptual approach to the hearing experience. This dissertation deals in a first part with some particular aspects related to the binaural spatial reproduction of sound, such as listening with headphones and the customization of the Head Related Transfer Function (HRTF). A study has been carried out on the influence of headphones on the perception of spatial impression and quality, with particular attention to the effects of equalization and subsequent non-linear distortion. With regard to the individualization of the HRTF a complete implementation of a HRTF measurement system is presented, and a new method for the measurement of HRTF in non-anechoic conditions is introduced. In addition, two different and complementary experiments have been carried out resulting in two tools that can be used in HRTF individualization processes, a parametric model of the HRTF magnitude and an Interaural Time Difference (ITD) scaling adjustment. In a second part concerning loudspeaker reproduction, different techniques such as Wave-Field Synthesis (WFS) or amplitude panning have been evaluated. With perceptual experiments it has been studied the capacity of these systems to produce a sensation of distance, and the spatial acuity with which we can perceive the sound sources if they are spectrally split and reproduced in different positions. The contributions of this research are intended to make these technologies more accessible to the general public, given the demand for audiovisual experiences and devices with increasing immersion.Gutiérrez Parera, P. (2020). Optimization and improvements in spatial sound reproduction systems through perceptual considerations [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/142696TESI