In-car speech recognition using distributed microphones: adapting to automatically detected driving conditions

In this paper, we describe a multichannel method of noisy speech recognition that can adapt to various in-car noise situations during driving. The method allows as 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 multiple 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 average error rate reductions of 43% in isolated word recognition under 15 different driving conditions.