Efficient, high-performance algorithms for N-Best search
HLT '90 Proceedings of the workshop on Speech and Natural Language
HLT '90 Proceedings of the workshop on Speech and Natural Language
Fast search algorithms for connected phone recognition using the stochastic segment model
HLT '90 Proceedings of the workshop on Speech and Natural Language
A simple statistical class grammar for measuring speech recognition performance
HLT '89 Proceedings of the workshop on Speech and Natural Language
The N-Best algorithm: an efficient procedure for finding top N sentence hypotheses
HLT '89 Proceedings of the workshop on Speech and Natural Language
Improvements in the stochastic segment model for Phoneme recognition
HLT '89 Proceedings of the workshop on Speech and Natural Language
Continuous speech recognition using segmental neural nets
HLT '91 Proceedings of the workshop on Speech and Natural Language
Training and scaling preference functions for disambiguation
Computational Linguistics
Diphone subspace mixture trajectory models for HMM Complementation
Speech Communication
HLT '91 Proceedings of the workshop on Speech and Natural Language
Recognition using classification and segmentation scoring
HLT '91 Proceedings of the workshop on Speech and Natural Language
Weight estimation for N-best rescoring
HLT '91 Proceedings of the workshop on Speech and Natural Language
Prosody/parse scoring and its application in ATIS
HLT '93 Proceedings of the workshop on Human Language Technology
Language modeling with sentence-level mixtures
HLT '94 Proceedings of the workshop on Human Language Technology
Combining knowledge sources to reorder N-best speech hypothesis lists
HLT '94 Proceedings of the workshop on Human Language Technology
HLT '94 Proceedings of the workshop on Human Language Technology
Sequentially finding the N-best list in hidden Markov models
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Effective use of linguistic and contextual information for statistical machine translation
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Discriminative corpus weight estimation for machine translation
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
New uses for the N-best sentence hypotheses within the BYBLOS speech recognition system
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
A speech understanding system based on statistical representation of semantics
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
Context modeling with the stochastic segment model
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
A Bayesian approach to speaker adaptation for the stochastic segment model
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
Speech recognition using segmental neural nets
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
Elliptical basis functions for segment modeling
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: plenary, special, audio, underwater acoustics, VLSI, neural networks - Volume I
Exploiting variable-width features in large vocabulary speech recognition
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II
Generating targeted paraphrases for improved translation
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Sections on Paraphrasing; Intelligent Systems for Socially Aware Computing; Social Computing, Behavioral-Cultural Modeling, and Prediction
| Hi-index | 0.00 |
This paper describes a general formalism for integrating two or more speech recognition technologies, which could be developed at different research sites using different recognition strategies. In this formalism, one system uses the N-best search strategy to generate a list of candidate sentences; the list is rescored by other systems; and the different scores are combined to optimize performance. Specifically, we report on combining the BU system based on stochastic segment models and the BBN system based on hidden Markov models. In addition to facilitating integration of different systems, the N-best approach results in a large reduction in computation for word recognition using the stochastic segment model.