Efficient time delay estimation and compensation applied to the cancellation of acoustic echo

The system identification problem is notably dealt with using adaptive filtering approaches. In many applications the unknown system response consists of an initial sequence of zero-valued coefficients that precedes the active part of the response. The presence of these coefficients introduces a flat delay in the incoming signals which can take significantly large values. When most adaptive approaches attempt to model such a system, the presence of flat delay impairs their operation and performance. The approach introduced in this thesis aims to model the flat delay and active part of the unknown system separately. An efficient system for time delay estimation (TDE) is introduced to estimate the flat delay of an unknown system. The estimated delay is then compensated within the adaptive system thus allowing the latter to cover the active part ofthe unknown system. The proposed system is applied to the Acoustic Echo Cancellation (ABC) problem

Distributed Microphone Array System for Two-way Audio Communication

Tässä työssä esitellään hajautettu mikrofoniryhmäjärjestelmä kahdensuuntaisessa äänikommunikaatiossa. Järjestelmän tavoitteena on paikallistaa hallitseva puhuja ja tallentaa puhesignaali mahdollisimman korkealaatuisesti. Työssä esiteltävässä järjestelmässä jokainen mikrofoniryhmä toimii polynomirakenteella parametrisoituna keilanmuodostajana (PBF), joka mahdollistaa jatkuvan keilanohjauksen. Hallitsevan puhelähteen suunta päätellään PBF:n jokaisen keilan ulostulotehoista. Lopuksi yhdistämällä jokaisen PBF:n kaikkien keilojen ulostulotehot muodostetaan avaruudellinen todennäköisyysfunktio (SLF), jonka suurin arvo määrää puhujan paikan. Puhesignaali tallennetaan ohjaamalla puhujaa lähinnä olevan PBF:n keila puhujan suuntaan. Tässä työssä esiteltävän järjestelmän toiminta arvioitiin simuloidulla ja mitatulla datalla. Arvionti näyttää, että toteutettu järjestelmä pystyy paikallistamaan puhujan noin 40 cm paikannustarkkuudella ja järjestelmä vaimentaa muista suunnista tulevia häiriölähteitä noin 15 dB. Lopuksi järjestelmä toteutettiin reaaliakaisena systeeminä Pure Data signaalinkäsittelyympäristössä.In this work a distributed microphone array system for two-way audio communication is presented. The goal of the system is to locate the dominant speaker and capture the speech signal with highest possible quality. In the presented system each microphone array works as a Polynomial Beamformer (PBF) thus enabling continuous beam steering. The output power of each PBF beam is used to determine the direction of the dominant speech source. Finally, a Spatial Likelihood Function (SLF) is formed by combining the output beam powers of each microphone array and the speaker is determined to be in the point that has highest value of SLF. The audio signal capture is done by steering the closest microphone array to the direction of the speaker. The presented audio capture front-end was evaluated with simulated and measured data. The evaluation shows that the implemented system gives approximately 40 cm localization accuracy and 15 dB attenuation of interference sources. Finally the system was implemented to run in real-time in the Pure Data signal processing environment

System Identification with Applications in Speech Enhancement

As the increasing popularity of integrating hands-free telephony on mobile portable devices and the rapid development of voice over internet protocol, identification of acoustic systems has become desirable for compensating distortions introduced to speech signals during transmission, and hence enhancing the speech quality. The objective of this research is to develop system identification algorithms for speech enhancement applications including network echo cancellation and speech dereverberation. A supervised adaptive algorithm for sparse system identification is developed for network echo cancellation. Based on the framework of selective-tap updating scheme on the normalized least mean squares algorithm, the MMax and sparse partial update tap-selection strategies are exploited in the frequency domain to achieve fast convergence performance with low computational complexity. Through demonstrating how the sparseness of the network impulse response varies in the transformed domain, the multidelay filtering structure is incorporated to reduce the algorithmic delay. Blind identification of SIMO acoustic systems for speech dereverberation in the presence of common zeros is then investigated. First, the problem of common zeros is defined and extended to include the presence of near-common zeros. Two clustering algorithms are developed to quantify the number of these zeros so as to facilitate the study of their effect on blind system identification and speech dereverberation. To mitigate such effect, two algorithms are developed where the two-stage algorithm based on channel decomposition identifies common and non-common zeros sequentially; and the forced spectral diversity approach combines spectral shaping filters and channel undermodelling for deriving a modified system that leads to an improved dereverberation performance. Additionally, a solution to the scale factor ambiguity problem in subband-based blind system identification is developed, which motivates further research on subbandbased dereverberation techniques. Comprehensive simulations and discussions demonstrate the effectiveness of the aforementioned algorithms. A discussion on possible directions of prospective research on system identification techniques concludes this thesis

Media gateway utilizando um GPU

Mestrado em Engenharia de Computadores e Telemátic

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

International audienc

Contextual awareness, messaging and communication in nomadic audio environments

Thesis (M.S.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1998.Includes bibliographical references (p. 119-122).Nitin Sawhney.M.S