Speaker independent phonetic transcription of fluent speech for large vocabulary speech recognition

Results are presented of experiments on speaker-independent phonetic transcription of fluent speech. The acoustic-phonetic model is a 38,505-parameter continuously variable duration hidden Markov model which allows real-time phonetic transcription to be performed by means of a modified Viterbi algorithm. The model was trained on 3020 sentences from the TIMIT database. Testing was performed on the remaining 180 sentences. In a test without lexical or syntactic constraints, the authors obtained 52% correct phonetic transcription with 12% insertions. The design of a system for recognition of fluent speech based on technique for phonetic transcription is described.