A Cache-Based Natural Language Model for Speech Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A statistical approach to machine translation
Computational Linguistics
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Exploiting syntactic structure for language modeling
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
A hybrid approach to adaptive statistical language modeling
HLT '94 Proceedings of the workshop on Human Language Technology
Language modeling with sentence-level mixtures
HLT '94 Proceedings of the workshop on Human Language Technology
Evaluating sense disambiguation across diverse parameter spaces
Natural Language Engineering
Empirical estimates of adaptation: the chance of two noriegas is closer to p/2 than p2
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Topic modeling in fringe word prediction for AAC
Proceedings of the 11th international conference on Intelligent user interfaces
Nonlocal language modeling based on context co-occurrence vectors
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
Corpus studies in word prediction
Proceedings of the 9th international ACM SIGACCESS conference on Computers and accessibility
Adaptive language modeling for word prediction
HLT-SRWS '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Student Research Workshop
Mixture-model adaptation for SMT
StatMT '07 Proceedings of the Second Workshop on Statistical Machine Translation
Lexical choice via topic adaptation for paraphrasing written language to spoken language
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
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This paper presents a novel method of generating and applying hierarchical, dynamic topic-based language models. It proposes and evaluates new cluster generation, hierarchical smoothing and adaptive topic-probability estimation techniques. These combined models help capture long-distance lexical dependencies. Experiments on the Broadcast News corpus show significant improvement in perplexity (10.5% overall and 33.5% on target vocabulary).