EUROSPEECH 2001 Scandinavia
Recently, multi-band automatic speech recognition (MBASR) has been proposed to combat environmental noises. We describe the two major efforts in the development of our asynchronous MBASR system for continuous speech recognition. Firstly, we successfully introduce asynchrony among sub-bands under the HMM composition framework. Secondly, the linear sub-band weightings are estimated by minimizing the string classification error among the N-best hypotheses using simulated noisy speech. When our asynchronous MBASR system is evaluated on connected TI digits with 0db additive low-pass white noise, compared with a full-band system, (1) our synchronous MBASR system reduces the absolute string error rate (SER) and word error rate (WER) by 19.8% and 14.1% respectively; (2) the introduction of asynchrony further reduces the absolute SER (WER) by 5.2%(2.5%); (3) an estimation of sub-band weightings using N-best string MCE training gives an additional reduction of absolute SER (WER) by 19.7% (5.1%).
Bibliographic reference. Tam, Yik-Cheung / Mak, Brian (2001): "Development of an asynchronous multi-band system for continuous speech recognition", In EUROSPEECH-2001, 575-578.