Fast search algorithms for connected phone recognition using the stochastic segment model
HLT '90 Proceedings of the workshop on Speech and Natural Language
Spoken language processing in the framework of human-machine communication at LIMSI
HLT '91 Proceedings of the workshop on Speech and Natural Language
Identification of non-linguistic speech features
HLT '93 Proceedings of the workshop on Human Language Technology
The LIMSI continuous speech dictation system
HLT '94 Proceedings of the workshop on Human Language Technology
Cross-lingual experiments with phone recognition
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II
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A series of experiments on speaker-independent phone recognition of continuous speech have been carried out using the recently recorded BREF corpus. These experiments are the first to use this large corpus, and are meant to provide a baseline performance evaluation for vocabulary-independent phone recognition of French. The HMM-based recognizer was trained with hand-verified data from 43 speakers. Using 35 context-independent phone models, a baseline phone accuracy of 60% (no phone grammar) was obtained on an independent test set of 7635 phone segments from 19 new speakers. Including phone bigram probabilities as phonotactic constraints resulted in a performance of 63.5%. A phone accuracy of 68.6% was obtained with 428 context dependent models and the bigram phone language model. Vocabulary-independent word recognition results with no grammar are also reported for the same test data.