Hands-Free Speech Recognition in a Noisy and Reverberant Environment

In this work a challenging scenario concerning hands-free continuos speech recognition is investigated. A set of experiments was carried out using microphone arrays having different numbers of omnidirectionl sensors and that were placed at different angles and distances from the talker. Both real and simulated array signals, obtained by means of the image method, were used. An enhanced input to a recognizer based on Hidden Markov Models was obtained by a time delay compensation module providing a beamformedsignal. HMM adaptation zs used to improve recognition performance in the various acoustic conditions