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» Improving Language Models by Clustering Training Sentences
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COLING
1996
13 years 9 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
14 years 2 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
EMNLP
2009
13 years 5 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
11 years 10 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
13 years 9 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