Sixth International Conference on Spoken Language Processing
October 16-20, 2000
Data-Driven Lexical Modeling of Pronunciation Variations for ASR
Qian Yang, Jean-Pierre Martens
ELIS-RUG, Gent, Belgium
In this paper a method for the automatic construction of a lexicon
with multiple entries per word is described. The basic idea is to
transform a reference word transcription by means of stochastic
pronunciation rules that can be learned automatically. This approach
already proved its potential (Cremelie & Martens, 1999),
and is now brought to a much higher level of performance. Relative
reductions of the word error rate (WER) of 20 % (open
vocabulary) to 45 % (closed vocabulary) are now within reach.
N. Cremelie, J.P. Martens. "In search for better pronunciation
models for speech recognition," Speech Communication
29, 115-136, 1999.
Yang, Qian / Martens, Jean-Pierre (2000):
"Data-driven lexical modeling of pronunciation variations for ASR",
In ICSLP-2000, vol.1, 417-420.