Thèse soutenue

Annulation d'écho acoustique pour terminaux mobiles à un et deux microphones

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Auteur / Autrice : Christelle Yemdji Tchassi
Direction : Nicholas W. D. Evans
Type : Thèse de doctorat
Discipline(s) : Signal et images
Date : Soutenance le 18/06/2013
Etablissement(s) : Paris, ENST
Ecole(s) doctorale(s) : École doctorale Informatique, télécommunications et électronique de Paris (1992-...)
Partenaire(s) de recherche : Laboratoire : Laboratoire Traitement et communication de l'information (Paris ; 2003-....)
Jury : Président / Présidente : Raymond Knopp
Examinateurs / Examinatrices : Christophe Beaugeant, Alexandre Guérin, Ludovick Lepauloux, Peter Vary
Rapporteurs / Rapporteuses : Marc Moonen, Patrick A. Naylor

Mots clés

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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.