Conference paper

DEORAS Anoop, MIKOLOV Tomáš and CHURCH Kenneth. A Fast Re-scoring Strategy to Capture Long-Distance Dependencies. In: Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing July 2011 Edinburgh, Scotland, UK. Edinburgh: Association for Computational Linguistics, 2011, pp. 1116-1127. ISBN 978-1-937284-11-4.
Publication language:english
Original title:A Fast Re-scoring Strategy to Capture Long-Distance Dependencies
Title (cs):Strategie pro rychlé reskórování se závislostmi přes dlouhé kontexty
Pages:1116-1127
Proceedings:Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing July 2011 Edinburgh, Scotland, UK
Conference:Conference on Empirical Methods in Natural Language Processing
Place:Edinburgh, GB
Year:2011
ISBN:978-1-937284-11-4
Publisher:Association for Computational Linguistics
URL:http://www.fit.vutbr.cz/research/groups/speech/publi/2011/deoras_emnlp2011_D11-1103.pdf [PDF]
URL:http://www.aclweb.org/anthology-new/D/D11/D11-1103.pdf [PDF]
Keywords
language model, re-scoring strategy, recurrent neural network
Annotation
The paper describes novel approach to lattice rescoring with complex lanaguage models with long-distance dependencies, such as recurrent neural network language models.
Abstract
A re-scoring strategy is proposed that makes it feasible to capture more long-distance dependencies in the natural language. Two pass strategies have become popular in a number of recognition tasks such as ASR (automatic speech recognition), MT (machine translation) and OCR (optical character recognition). The first pass typically applies a weak language model (n-grams) to a lattice and the second pass applies a stronger language model to N-best lists. The stronger language model is intended to capture more longdistance dependencies. The proposed method uses RNN-LM (recurrent neural network language model), which is a long span LM, to rescore word lattices in the second pass. A hill climbing method (iterative decoding) is proposed to search over islands of confusability in the word lattice. An evaluation based on Broadcast News shows speedups of 20 over basic N-best re-scoring, and word error rate reduction of 8% (relative) on a highly competitive setup.
BibTeX:
@INPROCEEDINGS{
   author = {Anoop Deoras and Tom{\'{a}}{\v{s}} Mikolov and Kenneth
	Church},
   title = {A Fast Re-scoring Strategy to Capture Long-Distance
	Dependencies},
   pages = {1116--1127},
   booktitle = {Proceedings of the 2011 Conference on Empirical Methods in
	Natural Language Processing July 2011 Edinburgh, Scotland,
	UK},
   year = {2011},
   location = {Edinburgh, GB},
   publisher = {Association for Computational Linguistics},
   ISBN = {978-1-937284-11-4},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php?id=9687}
}

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