In-car Speech Recognition Using Distributed Microphones
Tetsuya Shinde, Kazuya Takeda, Fumitada Itakura · Kluwer Academic Publishers eBooks · 2005
In this paper, we describe a method for multichannel noisy speech recognition that can adapt to various in-car noise situations during driving. Our proposed technique enables us to estimate the log spectrum of speech at a close-talking microphone based on the multiple regression of the log spectra (MRLS) of noisy signals captured by a set of distributed microphones. Through clustering of the spatial noise distributions under various driving conditions, the regression weights for MRLS are effectively adapted to the driving conditions. The experimental evaluation shows an average error rate reduction of 43 % in isolated word recognition under 15 different driving conditions.