Stereophonic acoustic echo cancellation employing selective-tap adaptive algorithms

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In Car Audio

This chapter presents implementations of advanced in Car Audio Applications. The system is composed by three main different applications regarding the In Car listening and communication experience. Starting from a high level description of the algorithms, several implementations on different levels of hardware abstraction are presented, along with empirical results on both the design process undergone and the performance results achieved

Convergence Analysis of Stereophonic Echo Canceller with Pre-Processing - Relation between Pre-Processing and Convergence -

This paper presents convergence characteristics of stereophonic echo cancellers with pre-processing. The convergence analysis of the averaged tap-weights show that the convergence characteristics depends on the relation between the impulse response in the far-end room and the changes of the pre-processing filters. Examining the uniqueness of the solution in the frequency domain leads us to the same relation. Computer simulation results show the validity of these analyses

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

Low Power Digital Filter Implementation in FPGA

Digital filters suitable for hearing aid application on low power perspective have been developed and implemented in FPGA in this dissertation. Hearing aids are primarily meant for improving hearing and speech comprehensions. Digital hearing aids score over their analog counterparts. This happens as digital hearing aids provide flexible gain besides facilitating feedback reduction and noise elimination. Recent advances in DSP and Microelectronics have led to the development of superior digital hearing aids. Many researchers have investigated several algorithms suitable for hearing aid application that demands low noise, feedback cancellation, echo cancellation, etc., however the toughest challenge is the implementation. Furthermore, the additional constraints are power and area. The device must consume as minimum power as possible to support extended battery life and should be as small as possible for increased portability. In this thesis we have made an attempt to investigate possible digital filter algorithms those are hardware configurable on low power view point. Suitability of decimation filter for hearing aid application is investigated. In this dissertation decimation filter is implemented using ‘Distributed Arithmetic’ approach.While designing this filter, it is observed that, comb-half band FIR-FIR filter design uses less hardware compared to the comb-FIR-FIR filter design. The power consumption is also less in case of comb-half band FIR-FIR filter design compared to the comb-FIR-FIR filter. This filter is implemented in Virtex-II pro board from Xilinx and the resource estimator from the system generator is used to estimate the resources. However ‘Distributed Arithmetic’ is highly serial in nature and its latency is high; power consumption found is not very low in this type of filter implementation. So we have proceeded for ‘Adaptive Hearing Aid’ using Booth-Wallace tree multiplier. This algorithm is also implemented in FPGA and power calculation of the whole system is done using Xilinx Xpower analyser. It is observed that power consumed by the hearing aid with Booth-Wallace tree multiplier is less than the hearing aid using Booth multiplier (about 25%). So we can conclude that the hearing aid using Booth-Wallace tree multiplier consumes less power comparatively. The above two approached are purely algorithmic approach. Next we proceed to combine circuit level VLSI design and with algorithmic approach for further possible reduction in power. A MAC based FDF-FIR filter (algorithm) that uses dual edge triggered latch (DET) (circuit) is used for hearing aid device. It is observed that DET based MAC FIR filter consumes less power than the traditional (single edge triggered, SET) one (about 41%). The proposed low power latch provides a power saving upto 65% in the FIR filter. This technique consumes less power compared to previous approaches that uses low power technique only at algorithmic abstraction level. The DET based MAC FIR filter is tested for real-time validation and it is observed that it works perfectly for various signals (speech, music, voice with music). The gain of the filter is tested and is found to be 27 dB (maximum) that matches with most of the hearing aid (manufacturer’s) specifications. Hence it can be concluded that FDF FIR digital filter in conjunction with low power latch is a strong candidate for hearing aid application

Advanced automatic mixing tools for music

PhDThis thesis presents research on several independent systems that when combined together can generate an automatic sound mix out of an unknown set of multi‐channel inputs. The research explores the possibility of reproducing the mixing decisions of a skilled audio engineer with minimal or no human interaction. The research is restricted to non‐time varying mixes for large room acoustics. This research has applications in dynamic sound music concerts, remote mixing, recording and postproduction as well as live mixing for interactive scenes. Currently, automated mixers are capable of saving a set of static mix scenes that can be loaded for later use, but they lack the ability to adapt to a different room or to a different set of inputs. In other words, they lack the ability to automatically make mixing decisions. The automatic mixer research depicted here distinguishes between the engineering mixing and the subjective mixing contributions. This research aims to automate the technical tasks related to audio mixing while freeing the audio engineer to perform the fine‐tuning involved in generating an aesthetically‐pleasing sound mix. Although the system mainly deals with the technical constraints involved in generating an audio mix, the developed system takes advantage of common practices performed by sound engineers whenever possible. The system also makes use of inter‐dependent channel information for controlling signal processing tasks while aiming to maintain system stability at all times. A working implementation of the system is described and subjective evaluation between a human mix and the automatic mix is used to measure the success of the automatic mixing tools

Proceedings of the EAA Spatial Audio Signal Processing symposium: SASP 2019

International audienc

Cancelación de Ecos Multicanal

La idea básica de la cancelación de ecos es bloquear la señal desde la sala remota para que no se realimente. Para ello se coloca un sistema adaptativo en medio que genere “idealmente” la misma señal que proviene de la sala local y se envía de vuelta a la sala remota la diferencia entre la señal estimada y la que retorna de la sala local, en lugar de esta última. La introducción de múltiples canales permite capturar la espacialidad de los locutores pero introduce una alta correlación entre las señales que afecta el comportamiento del cancelador adaptativo. Este inconveniente de mal condicionamiento del sistema, conocido como problema de la no‐unicidad, puede hacer incluso que el sistema adaptativo converja a una solución no única. En la cancelación de ecos multicanal estas soluciones no sólo dependen de las respuestas al impulso de la sala local, sino también de las respuestas al impulso de la sala remota. Las respuestas al impulso de las salas típicas en aplicaciones manos libres, que requieren de la cancelación de ecos, son extremadamente grandes (del orden de miles de coeficientes). La enorme longitud de las respuestas al impulso no sólo se traduce en un gran volumen de operaciones matemáticas sino también en un retardo inadmisible perceptualmente. En la primera parte de esta tesis se estudia el problema de la cancelación de ecos acústicos multicanal. A continuación se exploran y comparan diferentes técnicas de filtrado adaptativo multicanal en la búsqueda de la idoneidad para la aplicación de la cancelación de ecos. Para ello se establecen ocho experimentos: el primero y el cuarto, de un solo canal (caso más simple); el segundo, quinto y séptimo, de dos canales (caso estéreo: más simple del caso multicanal general); el tercero, sexto y octavo, de cinco canales (caso multicanal típico en aplicaciones domésticas y de videoconferencia). Los experimentos son elegidos de manera tal que constituyan casos críticos con una muy elevada correlación inter‐canal para poder estimar el comportamiento de los algoritmos en una situación muy crítica. Estas técnicas de filtrado adaptativo no pueden ser aplicadas directamente a un sistema de cancelación de ecos acústicos multicanal adaptativo por el retardo y la carga computacional que imponen las largas respuestas al impulso acústicas involucradas. Por ello, en la segunda parte de la tesis, se estudian arquitecturas de filtrado adaptativo multirresolución para abordar el problema en el dominio del tiempo y la frecuencia: descomposición en subbandas y filtrado adaptativo en el dominio de la frecuencia particionado por bloques. Por último se hace un estudio para la decorrelación inter‐canal que busca un mejor condicionamiento del problema: la decorrelación mediante la transformación adaptativa de Karhunen‐Loève y la introducción de ruido de banda ancha decorrelado. Esta última técnica permite afrontar el problema de la cancelación de ecos multicanal sin detección de doble locución. Finalmente se intenta buscar una valoración subjetiva de los resultados. En los apéndices se tratan dos temas muy importantes para el desarrollo de esta tesis. El primero trata de la simulación y medición de salas. Ambas técnicas son muy importantes para la cancelación de ecos multicanal porque permiten disponer de respuestas al impulso en diferentes condiciones, correlación, etc. sobre las que basar las simulaciones de los algoritmos desarrollados y analizados en la tesis. La segunda trata de las técnicas de gradiente conjugado que, aunque son un algoritmo de optimización para la minimización de funciones, por su importancia en esta investigación merece un estudio detallado. El uso de las técnicas de gradiente conjugado en la cancelación de ecos acústicos multicanal es uno de los aportes fundamentales de esta investigación y de ello se derivan diferentes algoritmos adaptativos

Effects of errorless learning on the acquisition of velopharyngeal movement control

Session 1pSC - Speech Communication: Cross-Linguistic Studies of Speech Sound Learning of the Languages of Hong Kong (Poster Session)The implicit motor learning literature suggests a benefit for learning if errors are minimized during practice. This study investigated whether the same principle holds for learning velopharyngeal movement control. Normal speaking participants learned to produce hypernasal speech in either an errorless learning condition (in which the possibility for errors was limited) or an errorful learning condition (in which the possibility for errors was not limited). Nasality level of the participants’ speech was measured by nasometer and reflected by nasalance scores (in %). Errorless learners practiced producing hypernasal speech with a threshold nasalance score of 10% at the beginning, which gradually increased to a threshold of 50% at the end. The same set of threshold targets were presented to errorful learners but in a reversed order. Errors were defined by the proportion of speech with a nasalance score below the threshold. The results showed that, relative to errorful learners, errorless learners displayed fewer errors (50.7% vs. 17.7%) and a higher mean nasalance score (31.3% vs. 46.7%) during the acquisition phase. Furthermore, errorless learners outperformed errorful learners in both retention and novel transfer tests. Acknowledgment: Supported by The University of Hong Kong Strategic Research Theme for Sciences of Learning © 2012 Acoustical Society of Americapublished_or_final_versio