Demisyllable-based HMM spotting for continuous speech recognition

The authors describe the acoustic processor of a Spanish continuous speech recognition system based on demisyllable units. The acoustic processor is based on a spotting algorithm which takes as input the unknown utterance, the HMM (hidden Markov model) of the reference demisyllables, and the lexical knowledge in terms of a finite state network. The spotting algorithm is a modified version of the one-step Viterbi algorithm with multiple hypotheses. The output of the system is a lattice of word hypotheses suitable to be parsed by a linguistic analyzer. The proposed acoustic processor was tested using the integers from 0 to 1000 and telephonic numbers in a speaker-independent approach. The results show the good performance of the demisyllable as a recognition unit for the Spanish language and the efficiency of the spotting algorithm.