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Comparison of performance of enhanced morpheme-based language model with different word-based language models for improving the performance of Tamil speech recognition system

Developing lexicographic sorting: An example for Urdu

Topic tracking based on bilingual comparable corpora and semisupervised clustering

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ACM Transactions on Asian Language Information Processing (TALIP) : Volume 5

ACM Transactions on Asian Language Information Processing (TALIP) : Volume 4

ACM Transactions on Asian Language Information Processing (TALIP) : Volume 3

ACM Transactions on Asian Language Information Processing (TALIP) : Volume 2

ACM Transactions on Asian Language Information Processing (TALIP) : Volume 1

Comparison of performance of enhanced morpheme-based language model with different word-based language models for improving the performance of Tamil speech recognition system

Content Provider	ACM Digital Library
Author	Saraswathi, S. Geetha, T. V.
Copyright Year	2007
Abstract	This paper describes a new technique of language modeling for a highly inflectional Dravidian language, Tamil. It aims to alleviate the main problems encountered in processing of Tamil language, like enormous vocabulary growth caused by the large number of different forms derived from one word. The size of the vocabulary was reduced by, decomposing the words into stems and endings and storing these sub word units (morphemes) in the vocabulary separately. A enhanced morpheme-based language model was designed for the inflectional language Tamil. The enhanced morpheme-based language model was trained on the decomposed corpus. The perplexity and Word Error Rate (WER) were obtained to check the efficiency of the model for Tamil speech recognition system. The results were compared with word-based bigram and trigram language models, distance based language model, dependency based language model and class based language model. From the results it was analyzed that the enhanced morpheme-based trigram model with Katz back-off smoothing effect improved the performance of the Tamil speech recognition system when compared to the word-based language models.
File Format	PDF
ISSN	15300226
e-ISSN	15583430
DOI	10.1145/1290002.1290003
Volume Number	6
Issue Number	3
Journal	ACM Transactions on Asian Language Information Processing (TALIP)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2007-11-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Language model Morphemes Perplexity Word error rate and speech recognition
Content Type	Text
Resource Type	Article
Subject	Computer Science

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