Abstract
A contribution for speaker-independent recognition systems is presented, as well for speech recognition in the presence of large vocabularies as for word spotting. The recognition strategy used is based upon continuous hidden markov models (HMMs) which include two levels (phonemic level and word level). The aim of the method is double; first to provide a fast algorithm for sub-vocabulary preselection or recognition in the presence of small vocabulary, second to improve the temporal control of the standard HMMs.
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