Pronunciation Modeling and Lexicon Adaptation for Spoken Language Technology (PMLA) September 14-15, 2002 Aspen Lodge, Estes Park, Colorado, USA

Modeling Pronunciation Variation for Cantonese Speech Recognition

Patgi Kam, Tan Lee

Department of Electronic Engineering, The Chinese University of Hong Kong

Due to the large variability of pronunciation in spontaneous speech, pronunciation modeling becomes a more challenging and essential part in speech recognition. In this paper, we describe two different approaches of pronunciation modeling by using decision tree. At lexical level, a pronunciation variation dictionary is built to obtain alternative pronunciations for each word, in which each entry is associated with a variation probability. At decoding level, decision tree pronunciation models are applied to expand the search space to include alternative pronunciations. Relative error reduction of 7.21% and 4.81% could be achieved at lexical level and decoding level respectively. The results at the two different levels are compared and contrasted.

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Bibliographic reference.  Kam, Patgi / Lee, Tan (2002): "Modeling pronunciation variation for Cantonese speech recognition", In PMLA-2002, 12-17.