Here is presented a phonetic source model whose parameters, estimated from phonetically transcribed texts, reflect the non-stationary phoneme conditional probability which is proper of a given language. Such a model will give a priori knowledges about the allowed phonetic sequences probabilities for a very large vocabulary speech recognizer, where the lexical access is made after phonetic decoding. After a discussion about the probability estimation method, model features and performances are given.
A word like phonetic sequence statistical source model for large lexicon automatic speech recognition systems / Falaschi, Alessandro. - STAMPA. - 1:(1987), pp. 167-170. (Intervento presentato al convegno European Conference on Speech Technology tenutosi a Edinburgh, Scotland, UK nel September 1987).
A word like phonetic sequence statistical source model for large lexicon automatic speech recognition systems
FALASCHI, Alessandro
1987
Abstract
Here is presented a phonetic source model whose parameters, estimated from phonetically transcribed texts, reflect the non-stationary phoneme conditional probability which is proper of a given language. Such a model will give a priori knowledges about the allowed phonetic sequences probabilities for a very large vocabulary speech recognizer, where the lexical access is made after phonetic decoding. After a discussion about the probability estimation method, model features and performances are given.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.