Skip to Main content Skip to Navigation
Book sections

Evolutionary Speech Recognition

Anne Spalanzani 1
1 E-MOTION - Geometry and Probability for Motion and Action
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : Automatic speech recognition systems are becoming ever more common and are increasingly deployed in more variable acoustic conditions, by very different speakers. So these systems, generally conceived in a laboratory, must be robust in order to provide optimal performance in real situations. This article explores the possibility of gaining robustness by designing speech recognition systems able to auto-modify in real time, in order to adapt to the changes of acoustic environment. As a starting point, the adaptive capacities of living organisms were considered in relation to their environment. Analogues of these mechanisms were then applied to automatic speech recognition systems. It appeared to be interesting to imagine a system adapting to the changing acoustic conditions in order to remain effective regardless of its conditions of use.
Complete list of metadata
Contributor : Anne Spalanzani Connect in order to contact the contributor
Submitted on : Thursday, October 11, 2007 - 3:42:19 PM
Last modification on : Thursday, October 21, 2021 - 3:51:39 AM


  • HAL Id : inria-00178574, version 1



Anne Spalanzani. Evolutionary Speech Recognition. Grimm and Kroschel. Robust Speech Recognition and Understanding, I-Tech, 2007. ⟨inria-00178574⟩



Record views