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» Improving Language Models by Clustering Training Sentences
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96
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COLING
1996
15 years 1 months ago
Modeling Topic Coherence for Speech Recognition
Statistical language models play a major role in current speech recognition systems. Most of these models have focussed on relatively local interactions between words. Recently, h...
Satoshi Sekine
ICASSP
2008
IEEE
15 years 7 months ago
Language modeling for voice search: A machine translation approach
This paper presents a novel approach to language modeling for voice search based on the idea and method of statistical machine translation. We propose an n-gram based translation ...
Xiao Li, Yun-Cheng Ju, Geoffrey Zweig, Alex Acero
102
Voted
EMNLP
2009
14 years 10 months ago
Less is More: Significance-Based N-gram Selection for Smaller, Better Language Models
The recent availability of large corpora for training N-gram language models has shown the utility of models of higher order than just trigrams. In this paper, we investigate meth...
Robert C. Moore, Chris Quirk
ACL
2012
13 years 2 months ago
Fast and Robust Part-of-Speech Tagging Using Dynamic Model Selection
This paper presents a novel way of improving POS tagging on heterogeneous data. First, two separate models are trained (generalized and domain-specific) from the same data set by...
Jinho D. Choi, Martha Palmer
NAACL
2003
15 years 1 months ago
Semantic Language Models for Topic Detection and Tracking
In this work, we present a new semantic language modeling approach to model news stories in the Topic Detection and Tracking (TDT) task. In the new approach, we build a unigram la...
Ramesh Nallapati