The design of current acoustic-phonetic decoders for a specific language involves the selection of an adequate set of sub-lexical units and the choice of the mathematical framework in order to model such units.This paper deals with both items. On the one hand, we will discuss the choice of sub-lexical units we made for a Spanish continuous speech decoder. Our goal was to build a general, vocabulary-independent, speaker independent Spanish Continuous Speech phonetic decoder with only sublexical knowledge. For this purpose, we used a corpus of 1700 Spanish sentences uttered by 10 speakers.On the other hand and within the framework of the Semicontinuous Hidden Markov Modeling, we will discuss different approaches to the Viterbi-based re-estimation procedure. In this case we aimed to take advantage of the jointly optimization of the codebook together with the parameters of the model as well as reducing the computation cost of updating the codebook in the training phase.* This work has been partially supported by grants TIC 448/89 and TIC 1026/92-C02 of the Spanish CICYT.
11-5150-7803-0946-4193 $3.00 0 1993 IEEE
This paper describes the work carried out to select the most suitable set of Sublexical Units for Continuous Speech Recognition of Basque. Even if there are several dialects in Basque, only one of them has been used to choose the preliminary set of sounds. Bearing in mind this aim, a wide experimentation has been carried out to select Context Independent Phone-Like Units. Then, in order to obtain robust acoustic models for the language, the units have been evaluated with most of the dialectal variants of Basque. Finally, Decision-Trees based Context Dependent Sublexical Units are selected. For building the trees the classical methodology of Bahl and the efficient Growing and Pruning algorithm have been used.
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