Improvements On Speech Recogniton For Fast Talkers

Improvements On Speech Recogniton For Fast Talkers (1999)

by Matthew Richardson , Mei-Yuh Hwang , Alex Acero , Xuedong Huang

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Datum	Value	Source
TITLE	Improvements On Speech Recogniton For Fast Talkers	user correction - Legacy Corrections
AUTHOR NAME	Matthew Richardson	user correction - Legacy Corrections
AUTHOR NAME	Mei-Yuh Hwang	user correction - Legacy Corrections
AUTHOR NAME	Alex Acero	user correction - Legacy Corrections
AUTHOR NAME	Xuedong Huang	user correction - Legacy Corrections
ABSTRACT	The accuracy of a speech recognition (SR) system depends on many factors, such as the presence of background noise, mismatches in microphone and language models, variations in speaker, accent and even speaking rates. In addition to fast speakers, even normal speakers will tend to speak faster when using a speech recognition system in order to get higher throughput. Unfortunately, state-of-the-art SR systems perform significantly worse on fast speech. In this paper, we present our efforts in making our system more robust to fast speech. We propose cepstrum length normalization, applied to the incoming testing utterances, which results in a 13% word error rate reduction on an independent evaluation corpus. Moreover, this improvement is additive to the contribution of Maimum Likelihood Linear Regression (MLLR) adaptation. Together with MLLR, a 23% error rate reduction was achieved	user correction - Legacy Corrections
YEAR	1999	user correction - Legacy Corrections
CITATIONS	8 found	ParsCit 1.0