Joint evaluation of multiple speech patterns for speech recognition and training
Computer Speech and Language
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This paper proposes simultaneous decoding using multiple utterances to derive one or more allophonic transcriptions for each word. Three possible simultaneous decoding algorithms, namely the N-best-based algorithm, the forward-backward-based algorithm and the word-network-based algorithm, are outlined. The proposed word-network-based algorithm can incrementally decode a transcription from any number of training utterances. Speech recognition experiments for both known and unknown word vocabularies show up to 16% reduction in word error rate when simultaneously decoded allophonic transcriptions are added to the recognition dictionaries. This result holds even for dictionaries originally transcribed by expert phoneticians.