Speech recognition under noisy environments using multiple microphones based on asynchronous and intermittent measurements

We propose a robust speech recognition method under noisy environments using multiple microphones based on asynchronous and intermittent observation. In asynchronous and intermittent observation, the noise spectrum is estimated by the environmental noise observed in fragments from multiple microphones, and spectral subtraction is performed by this estimated noise spectrum. In this paper, we consider the case of estimating the noise spectrum from the noise observed by another microphone just before speech input. However, the noise spectrum needs to be compensated because of the difference in the location of the microphone in this case. Then, we examined compensating the noise spectrum by using the estimated LSFL on the log spectrum. By compensating the noise spectrum, the recognition rate improved compared with the case without compensation.