8th International Conference on Spoken Language Processing

Jeju Island, Korea
October 4-8, 2004

Improving Automatic Speech Recognition Performance and Speech Inteligibility with Harmonicity based Dereverberation

Keisuke Kinoshita, Tomohiro Nakatani, Masato Miyoshi

NTT Corporation, Japan

A speech signal captured by a distant microphone is generally smeared by reverberation, that severely degrades both the speech intelligibility and Automatic Speech Recognition (ASR) performance. Previously, we proposed a novel dereverberation method, named "Harmonicity based dEReverBeration (HERB)", which estimates the inverse filter of an unknown impulse response by utilizing the inherent speech property, harmonics. In this paper, we carry out a formal evaluation of speech intelligibility for dereverberated speech, and further investigate HERB's possibilities to improve ASR performance. Experimental results show that HERB is able to improve speech intelligibility to the level of clean speech. HERB is also found to be very effective at improving ASR performance, even under unknown severe reverberant environments by being used with MLLR and a multicondition acoustic model.

Full Paper

Bibliographic reference.  Kinoshita, Keisuke / Nakatani, Tomohiro / Miyoshi, Masato (2004): "Improving automatic speech recognition performance and speech inteligibility with harmonicity based dereverberation", In INTERSPEECH-2004, 2649-2652.