IEEE Transactions on Pattern Analysis and Machine Intelligence
Class-based n-gram models of natural language
Computational Linguistics
Statistical methods for speech recognition
Statistical methods for speech recognition
An efficient method for determining bilingual word classes
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
A phrase-based, joint probability model for statistical machine translation
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
A variable-length category-based n-gram language model
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01
Estimation of stochastic context-free grammars and their use as language models
Computer Speech and Language
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In this work, we propose and formulate two different approaches for the language model integrated in a Continuous Speech Recognition System. Both of them make use of class-based language models where classes are made up of segments or sequences of words. On the other hand, an interpolated model of a class-based language model and a word-based language model is explored as well. The experiments carried out over a spontaneous dialogue corpus in Spanish, demonstrate that introducing segments of words in a class-based language model a better performance of a Continuous Speech Recognition system can be achieved.