The objective of the research is to achieve a systematic combination of acoustic echo reduction components that together achieve a robust performance of the MCAEC system as a whole. Conventional approaches to the acoustic echo reduction system typically assume that individual components would perform ideally. For example, the adaptive algorithm for AEC is often developed in the absence of strong near-end signal, the algorithm for RES is often an added module that is developed as a separate noise reduction component, and the decorrelation procedure for MCAEC is yet another add-on module that simply introduces some form of distortion to the reference signal. The main challenge is in designing a consistent criterion across all modules that can be jointly optimized to form a more consistent framework for acoustic echo reduction. The decorrelation procedure can potentially benefit from the system approach as well if it is designed by taking the near-end listener into account. The MCAEC system should be optimized not only for the echo cancellation and suppression performance, but also for the reference signal quality after the added distortion from the decorrelation procedure. Finally, a tuning strategy is presented to jointly optimize the parameters across all modules using object criteria.

Ever since the birth of the telephony system, the problem with echoes, arising from impedance mismatch in 2/4-wire hybrids, or acoustic echoes where a loudspeaker signal is picked up by a closely located microphone, has been ever present. The removal of these echoes is crucial in order to achieve an acceptable audio quality for conversation. Today, the perhaps most common way for echo removal is through cancellation, where an adaptive filter is used to produce an estimated replica of the echo which is then subtracted from the echo-infested signal. Echo cancellation in practice requires extensive control of the filter adaptation process in order to obtain as rapid convergence as possible while also achieving robustness towards disturbances. Moreover, despite the rapid advancement in the computational capabilities of modern digital signal processors there is a constant demand for low-complexity solutions that can be implemented using low power and low cost hardware. This thesis presents low-complexity solutions for echo cancellation related to both the actual filter adaptation process itself as well as for controlling the adaptation process in order to obtain a robust system. Extensive simulations and evaluations using real world recorded signals are used to demonstrate the performance of the proposed solutions.

<p>The acoustic echo problem arises whenever there is acoustic coupling between a loudspeaker and a microphone, such as in a teleconference system. This problem is traditionally solved by using an acoustic echo canceler (AEC), which models the echo path with adaptive filters. Long adaptive filters are necessary for satisfactory echo cancellation, which makes AEC highly computationally complex. Recently, a low-complexity echo suppression scheme was presented, the perceptual acoustic echo suppressor (PAES). Spectral modification is used to suppress the echoes, and the complexity is reduced by incorporating perceptual theories. However, under ideal conditions AEC performs better than PAES. </p><p>This thesis considers a hybrid system, which combines AEC and PAES. AEC is used to cancel low-frequency echo components, while PAES suppresses high-frequency echo components. The hybrid system is simulated and assessed, both through subjective listening tests and objective evaluations. The hybrid scheme is shown to have virtually the same perceived quality as a full-band AEC, while having a significantly lower complexity and a higher degree of robustness.</p>

The acoustic echo problem arises whenever there is acoustic coupling between a loudspeaker and a microphone, such as in a teleconference system. This problem is traditionally solved by using an acoustic echo canceler (AEC), which models the echo path with adaptive filters. Long adaptive filters are necessary for satisfactory echo cancellation, which makes AEC highly computationally complex. Recently, a low-complexity echo suppression scheme was presented, the perceptual acoustic echo suppressor (PAES). Spectral modification is used to suppress the echoes, and the complexity is reduced by incorporating perceptual theories. However, under ideal conditions AEC performs better than PAES. This thesis considers a hybrid system, which combines AEC and PAES. AEC is used to cancel low-frequency echo components, while PAES suppresses high-frequency echo components. The hybrid system is simulated and assessed, both through subjective listening tests and objective evaluations. The hybrid scheme is shown to have virtually the same perceived quality as a full-band AEC, while having a significantly lower complexity and a higher degree of robustness.

The objective of this research is to presents new acoustic echo cancellation design methods that can effectively work in the nonlinear environment. Acoustic echo is an annoying issue for voice communication systems. Because of room acoustics and delay in the transmission path, echoes affect the sound quality and may hamper communications. Acoustic echo cancellers (AECs) are employed to remove the acoustic echo while keeping full-duplex communications. AEC designs face a variety of challenges, including long room impulse response, acoustic path nonlinearity, ambient noise, and double-talk situation. We investigate two parts of echo canceller design: echo cancellation algorithm design and control logic algorithm design. In the first part, our work focuses on the nonlinear adaptive and fast-convergence algorithms. We investigate three different structures: predistortion linearization, cascade structure, and nonlinear residual echo suppressor. Specifically, we are interested in the coherence function, since it provides a means for quantifying linear association between two stationary random processes. By using the coherence as a criterion to design the nonlinear echo canceller in the system, our method guarantees the algorithm stability and leads to a faster convergence rate. In the second part, our work focuses on the robustness of AECs in the presence of interference. With regard to the near-end speech, we investigate the double-talk detector (DTD) design in conjunction with nonlinear AECs. Specifically, we propose to design a DTD based on the mutual information (MI). We show that the advantage of the MI-based method, when compared with the existing methods, is that it is applicable to both the linear and nonlinear scenarios. With respect to the background noise, we propose a variable step-size and variable tap-length least mean square (LMS) algorithm. Based on the fact that the room impulse response usually exhibits an exponential decay power profile in acoustic echo cancellation applications, the proposed method finds optimal step size and tap length at each iteration. Thus, it achieves faster convergence rate and better steady-state performance. We show a number of experimental results to illustrate the performance of the proposed algorithms.

<p>Acoustic echo cancelation (AEC) composes a fundamental property of speech processing to enable a pleasant telecommunication conversation. Without this property of the telephone the communicator would hear an annoying echo of his own voice along with the speech from the other communicator. This would make a conversation through any telecommunication device an unpleasant experience.</p><p>AEC has been subject of interest since 1950s in the telecom industry and very efficient solutions were devised to cancel linear echo. With the advent of low cost hands free communication devices the issue of non linear echo became prominent because these devices use cheap loudspeakers that produce artifacts in addition to the desired sound which will cause non linear echo that cannot be cancelled by linear echo cancellers.</p><p>In this thesis a Harmonic Distortion Residual Echo Cancelation algorithm has been chosen for further investigations (HDRES). HDRES has many of those features that are desirable for an algorithm which is dealing with nonlinear acoustic echo cancelation, such as low computational complexity and fast convergence. The algorithm was first implemented in Matlab where it was tested and modified. The final result of the modified algorithm was then implemented in C and integrated with a complete AEC system. Before the implementation a number of measurements were done to distinguish the nonlinearities that were cause by the mobile phone loudspeaker. The measurements were performed on three different mobile pones which were documented to have problems with nonlinear acoustic echo.</p><p>The result of this thesis has shown that it might be possible to use an adaptive filter, which has both low complexity and fast convergence, in an operating AEC system. However, the request for such a system to work would be that a doubletalk detector is implemented along with the adaptive algorithm. That way the doubletalk situation could be found and the adaptation of the algorithm could be stopped. Thus, the major part of the speech would be saved.</p>

Acoustic echo cancelation (AEC) composes a fundamental property of speech processing to enable a pleasant telecommunication conversation. Without this property of the telephone the communicator would hear an annoying echo of his own voice along with the speech from the other communicator. This would make a conversation through any telecommunication device an unpleasant experience. AEC has been subject of interest since 1950s in the telecom industry and very efficient solutions were devised to cancel linear echo. With the advent of low cost hands free communication devices the issue of non linear echo became prominent because these devices use cheap loudspeakers that produce artifacts in addition to the desired sound which will cause non linear echo that cannot be cancelled by linear echo cancellers. In this thesis a Harmonic Distortion Residual Echo Cancelation algorithm has been chosen for further investigations (HDRES). HDRES has many of those features that are desirable for an algorithm which is dealing with nonlinear acoustic echo cancelation, such as low computational complexity and fast convergence. The algorithm was first implemented in Matlab where it was tested and modified. The final result of the modified algorithm was then implemented in C and integrated with a complete AEC system. Before the implementation a number of measurements were done to distinguish the nonlinearities that were cause by the mobile phone loudspeaker. The measurements were performed on three different mobile pones which were documented to have problems with nonlinear acoustic echo. The result of this thesis has shown that it might be possible to use an adaptive filter, which has both low complexity and fast convergence, in an operating AEC system. However, the request for such a system to work would be that a doubletalk detector is implemented along with the adaptive algorithm. That way the doubletalk situation could be found and the adaptation of the algorithm could be stopped. Thus, the major part of the speech would be saved.

Mobile terminals are arguably the most popular telecommunications device of the present day. With the expectation of use anytime, anywhere, mobile terminals are increasingly used in adverse scenarios such as in hands-free mode and in noisy environments. Speech quality is commonly degraded in such cases by the presence of acoustic echo and ambient noise. In consequence, mobile terminals are generally equipped with speech signal processing algorithms in order to assure acceptable speech quality. Classical approaches to speech signal processing involve independent acoustic echo cancellation, noise suppression and post-filtering. While performance is generally acceptable, degradations are noticeable at low signal-to-echo ratios (hands-free scenarios) and computational complexity can be high. Furthermore, while mobile terminals are increasingly equipped with multiple microphones, they are generally exploited for noise suppression alone, even if there is natural potential for combined noise suppression and echo control. This thesis presents new combination and synchronization architecture for acoustic echo cancellation for single- and dual-microphone devices. It moves beyond the current state-of-the-art by reducing computational complexity while improving performance in low signal-to-echo conditions. The thesis also presents the first dual-microphone solution to double-talk detection. These contributions pave the way for further applied research in speech processing; the novel architecture is readily extendible to multiple-microphone scenarios while respecting levels of computational efficiency required for integration in current mobile terminals. / Les téléphones mobiles sont sans aucun doute les terminaux de télécommunication le plus populaire de nos jours. Le besoin de mobilité étant toujours croissant, les téléphones mobiles sont parfois utilisés dans des conditions très adverses : mains-libres ou environnements bruités. Dans ces conditions, la qualité de la parole est perturbée par la présence de l'écho acoustique et du bruit ambiant. Les terminaux sont généralement équipés d'algorithmes de traitement de la parole afin de garantir une qualité de la parole acceptable. Composés d’un annuleur d’écho adaptatif, d’une réduction de bruit et d’une suppression d’écho résiduel, les chaines de traitement de parole classiques fournissent en général une qualité de la parole acceptable moyennant une complexité de calcul importante. Néanmoins, lorsque le rapport signal à écho est faible on peut noter des dégradations du signal utile. Les terminaux mobiles récents sont de plus en plus équipés de plusieurs microphones qui ne sont alors utilisés que pour la réduction de bruit bien qu’ils présentent un indéniable intérêt pour les systèmes de réduction conjointe de bruit et d’écho résiduel. Cette thèse présente une nouvelle architecture combinée d’annulation d’écho pour terminaux mobiles à un ou deux microphones. L’architecture proposée réduit efficacement la complexité de calcul tout en améliorant la qualité de la parole dans les scénarios défavorables. Nous présentons également la première solution bi-microphones de détection de double parole. Enfin, nos techniques bi-microphones peuvent facilement être appliquées aux terminaux multi-microphones et tout en ayant une capacité calculatoire acceptable pour les téléphones mobiles.

In system identification scenario, the linear approximation of the system modelled by its impulse response, is estimated in real time by gradient type Least Mean Square (LMS) or Recursive Least Squares (RLS) algorithms. In recent applications like acoustic echo cancellation, the order of the impulse response to be estimated is very high, and these traditional approaches are inefficient and real time implementation becomes difficult. Alternatively, the system is modelled by a set of shorter adaptive filters operating in parallel on subsampled signals. This approach, referred to as subband adaptive filtering, is expected to reduce not only the computational complexity but also to improve the convergence rate of the adaptive algorithm. But in practice, different subband adaptive algorithms have to be used to enhance the performance with respect to complexity, convergence rate and processing delay. A single subband adaptive filtering algorithm which outperforms the full band scheme in all applications is yet to be realized. This thesis is intended to study the subband adaptive filtering techniques and explore the possibilities of better algorithms for performance improvement. Three different subband adaptive algorithms have been proposed and their performance have been verified through simulations. These algorithms have been applied to acoustic echo cancellation and EEG artefact minimization problems. Details of the work To start with, the fast FIR filtering scheme introduced by Mou and Duhamel has been generalized. The Perfect Reconstruction Filter Bank (PRFB) is used to model the linear FIR system. The structure offers efficient implementation with reduced arithmetic complexity. By using a PRFB with non adjacent filters non overlapping, many channel filters can be eliminated from the structure. This helps in reducing the complexity of the structure further, but introduces approximation in the model. The modelling error depends on the stop band attenuation of the filters of the PRFB. The error introduced due to approximation is tolerable for applications like acoustic echo cancellation. The filtered output of the modified generalized fast filtering structure is given by (formula) where, Pk(z) is the main channel output, Pk,, k+1 (z) is the output of auxiliary channel filters at the reduced rate, Gk (z) is the kth synthesis filter and M the number of channels in the PRFB. An adaptation scheme is developed for adapting the main channel filters. Auxiliary channel filters are derived from main channel filters. Secondly, the aliasing problem of the classical structure is reduced without using the cross filters. Aliasing components in the estimated signal results in very poor steady state performance in the classical structure. Attempts to eliminate the aliasing have reduced the computation gain margin and the convergence rate. Any attempt to estimate the subband reference signals from the aliased subband input signals results in aliasing. The analysis filter Hk(z) having the following antialiasing property (formula) can avoid aliasing in the input subband signal. The asymmetry of the frequency response prevents the use of real analysis filters. In the investigation presented in this thesis, complex analysis filters and real'synthesis filters are used in the classical structure, to reduce the aliasing errors and to achieve superior convergence rate. PRFB is traditionally used in implementing Interpolated FIR (IFIR) structure. These filters may not be ideal for processing an input signal for an adaptive algorithm. As third contribution, the IFIR structure is modified using discrete finite frames. The model of an FIR filter s is given by Fc, with c = Hs. The columns of the matrix F forms a frame with rows of H as its dual frame. The matrix elements can be arbitrary except that the transformation should be implementable as a filter bank. This freedom is used to optimize the filter bank, with the knowledge of the input statistics, for initial convergence rate enhancement . Next, the proposed subband adaptive algorithms are applied to acoustic echo cancellation problem with realistic parameters. Speech input and sufficiently long Room Impulse Response (RIR) are used in the simulations. The Echo Return Loss Enhancement (ERLE)and the steady state error spectrum are used as performance measures to compare these algorithms with the full band scheme and other representative subband implementations. Finally, Subband adaptive algorithm is used in minimization of EOG (Electrooculogram) artefacts from measured EEG (Electroencephalogram) signal. An IIR filterbank providing sufficient isolation between the frequency bands is used in the modified IFIR structure and this structure has been employed in the artefact minimization scheme. The estimation error in the high frequency range has been reduced and the output signal to noise ratio has been increased by a couple of dB over that of the fullband scheme. Conclusions Efforts to find elegant Subband adaptive filtering algorithms will continue in the future. However, in this thesis, the generalized filtering algorithm could offer gain in filtering complexity of the order of M/2 and reduced misadjustment . The complex classical scheme offered improved convergence rate, reduced misadjustment and computational gains of the order of M/4 . The modifications of the IFIR structure using discrete finite frames made it possible to eliminate the processing delay and enhance the convergence rate. Typical performance of the complex classical case for speech input in a realistic scenario (8 channel case), offers ERLE of more than 45dB. The subband approach to EOG artefact minimization in EEG signal was found to be superior to their fullband counterpart. (Refer PDF file for Formulas)

Há um grande interesse hoje em desenvolver terminais viva-voz que permitam aos participantes de uma conversa à distância contarem com um bom grau de naturalidade e inteligibilidade. O objetivo deste trabalho é apresentar solução para dois impedimentos que surgem quando se deseja projetar um terminal viva-voz para ser utilizado em automóveis: o eco acústico resultante do acoplamento entre microfone e alto-falante do terminal; e o ruído ambiente produzido por exemplo pelo vento, pneus e motor do veículo. A solução proposta envolve o uso de filtros adaptativos e alterações no espectro do sinal de voz para minimizar os problemas mencionados. Os aspectos teóricos são abordados de forma breve, sem deixar no entanto que nenhum detalhe importante fique de fora. Uma implementação prática e eficiente em processador digital de sinais é um dos destaques do trabalho. / There is currently great motivation in developing hands-free devices which offer users, engaged in a telephone conversation, a good level of naturalness and intelligibility. In this work, the goal is to present a solution for two well-known problems that occur when designing a hands-free device for use in automobile environments: (1) the acoustic echo coupling between microphone and speaker, and (2) the background noise generated for example by wind, tires and vehicle engine. The proposed solution includes adaptive filtering techniques and modifications in the speech signal spectrum, in order to minimize the two problems above. Theoretical issues are briefly analyzed, however the author believes no relevant detail is kept out. Highlighted in the report is a practical and efficient implementation of the algorithms in a modern digital signal processor.