Automatic acquisition of names using speak and spell mode in spoken dialogue systems
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
Automatic phonetic transcription of large speech corpora
Computer Speech and Language
A dialogue approach to learning object descriptions and semantic categories
Robotics and Autonomous Systems
A joint decoding algorithm for multiple-example-based addition of words to a pronunciation lexicon
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
A new method for OOV detection using hybrid word/fragment system
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Contextual information improves OOV detection in speech
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
The ATR multilingual speech-to-speech translation system
IEEE Transactions on Audio, Speech, and Language Processing
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This paper presents a method called Interactive Phoneme Update (IPU) that enables users to teach systems the pronunciation (phoneme sequences) of words in the course of speech interaction. Using the method, users can correct mis-recognized phoneme sequences by repeatedly making correction utterances according to the system responses. The originalities of this method are: (1) word-segment-based correction that allows users to use word segments for locating mis-recognized phonemes based on open-begin-end dynamic programming matching and generalized posterior probability, (2) history-based correction that utilizes the information of phoneme sequences that were recognized and corrected previously in the course of interactive learning of each word. Experimental results show that the proposed IPU method reduces the error rate by a factor of three over a previously proposed maximum-likelihood-based method.