Combining connectionist multi-band and full-band probability streams for speech recognition of natural numbers

Abstract

Multi-band automatic speech recognition is a new and ex-ploratory area of speech recognition which has been getting much attention in the research community. It has been shown that multi-band ASR reduces word error in noisy conditions, particularly in the case of narrow band noise. In this work we show that multi-band ASR could be used to improve the speech recognition accuracy of natural numbers for clean speech when the multi-band (MB) information stream is used in addition to the full-band (FB) one. We also observe that a similar combination method significantly reduces the error rate on reverberant speech. Finally, we analyze the error patterns of the full-band and multi-band paradigms to understand why the combination of the two streams is effective.