Extracting Phoneme Pronunciation Information from Corpora

m l / / / / / / / / / Extracting Phoneme Pronunciation Information from Corpora Ian Thomas, Ingrid Zukerman Department of Computer Science Monash University Clayton, VICTORIA 3168 AUSTRALIA {iant, ingrid}@cs .monash. edu. au Bhavani Raskutti Artificial Intelligence Section Telstra Research Laboratories Clayton, VICTORIA 3168 AUSTRALIA b. raskutt i@trl, oz. au Abstract We present a procedure that determines a set of phonemes possibly intended by a speaker from a recognized or uttered phone. This in- formation will be used to allow a speech rec- ognizer to take pronunciation into account or to consider input from a noisy source during lexical access. We investigate the hypothesis that different pronunciations of a phone occur within groups of sounds physically produced the same way, and use the Minimum Message Length principle to consider the effect of a phoneme's context on its pronunciation. 1 Introduction When trying to match spoken words to dictionary entries during speech recognition, it is useful to be able to generate alternative versions of the spoken sequences of phones to account for the manner in which different speakers pronounce a phone. If we know the probabilities that the component sounds in a sequence of phones are pronounced like other sounds, then likely alternative pronunciations of that sequence of phones can be generated to match against a lexicon of known words. Furthermore, if we also have some idea of how the context within which a phone was uttered affects its pronunciation, we have extra information which can be used to pro- duce more realistic alternative pronunciations. This paper considers the task of automatically extracting statistical information about how vari- ous sound sections of words (phonemes) are pro- nounced by speakers (as phones) by matching in- tended phonemes and uttered phones from a tran- scribed speech corpus. The same approach could be used to gather statistics about how phones rec- ogaized (or mis-recognized) by a speech recognizer match the phonemes intended by a speaker. This information extraction process is part of the training phase for the lexical access component of a speech recognition system, where the pronunciation probabilities are generated from a training corpus. The study was done on the TIMIT corpus (Fisher et al., , 1986) -- a collection of American-English read sentences with correct time-aligned acoustic- phonetic and orthographic (word-aligned) transcrip- tions. 1 The corpus contains 3696 sentences spoken by 462 speakers from 8 different dialect divisions across the United States. Previous work by Riley (1989) and Withgott and Chen (1993) used Classification and Regression Trees (CART) on a large number of different features of the corpus (such as genderi dialect and speaking rate) to obtain pronunciation information of inten- ded phonemes. Our system obtain~ similar results using positional information and context, and us- ing exact matches from uttered phones to intended phonemes to guide other matches. Work by Cohen et (d., (1987) on pronunciation used a couple of set sentences for multiple speakers, but did not cover a wide range of words (and thus different phone contexts). …

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