Natural Language Modeling for Phoneme-to-Text Transcription
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multilevel decoding for very-large-size-dictionary speech recognition
IBM Journal of Research and Development
High level knowledge sources in usable speech recognition systems
Communications of the ACM
A dynamic language model for speech recognition
HLT '91 Proceedings of the workshop on Speech and Natural Language
Tagging accurately: don't guess if you know
ANLC '94 Proceedings of the fourth conference on Applied natural language processing
Does Baum-Welch re-estimation help taggers?
ANLC '94 Proceedings of the fourth conference on Applied natural language processing
A practical part-of-speech tagger
ANLC '92 Proceedings of the third conference on Applied natural language processing
Trigger-pair predictors in parsing and tagging
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Modeling topic coherence for speech recognition
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Augmenting a hidden Markov model for phrase-dependent word tagging
HLT '89 Proceedings of the workshop on Speech and Natural Language
Adaptive language modeling using minimum discriminant estimation
HLT '91 Proceedings of the workshop on Speech and Natural Language
Improvements in stochastic language modeling
HLT '91 Proceedings of the workshop on Speech and Natural Language
Adaptive language modeling using minimum discriminant estimation
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
| Hi-index | 0.00 |
This article describes two complementary models that represent dependencies between words in local and non-local contexts. The type of local dependencies considered are sequences of part of speech categories for words. The non-local context of word dependency considered here is that of word recurrence, which is typical in a text. Both are models of phenomena that are to a reasonable extent domain independent, and thus are useful for doing prediction in systems using large vocabularies.