Sixth European Conference on Speech Communication and Technology
In this paper, we present a markovian system, which takes into account pronunciation variation of French. After doing a brief overview of different methods allowing to deal with pronunciation variation in ASR, we describe our approach (which is based on the MHAT (Markovian Harmonic Adaptation and Transduction) model), as well as the lexical and phonological materials defined in order to implement MHAT into a classic ASR system based on HMM models. We finally compare two approaches (both issue from the MHAT model) that differ each other by the level of pronunciation modeling : at the lexicon level and at the language model level (by introducing an intermediate level of words representations depending on the context of words in the sentence). Results show an improvement of French continuous speech recognition when taking into account the context of words in the sentence within the language model.
Full Paper (PDF) Gnu-Zipped Postscript
Bibliographic reference. Brieussel-Pousse, Laure / Perennou, Guy (1999): "Language model level vs. lexical level for modeling pronunciation variation in a French CSR", In EUROSPEECH'99, 1771-1774.