Entry Saraswathi:2007:CPE from talip.bib

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BibTeX entry

@Article{Saraswathi:2007:CPE,
  author =       "S. Saraswathi and T. V. Geetha",
  title =        "Comparison of performance of enhanced morpheme-based
                 language model with different word-based language
                 models for improving the performance of {Tamil} speech
                 recognition system",
  journal =      j-TALIP,
  volume =       "6",
  number =       "3",
  pages =        "9:1--9:??",
  month =        nov,
  year =         "2007",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1290002.1290003",
  ISSN =         "1530-0226 (print), 1558-3430 (electronic)",
  ISSN-L =       "1530-0226",
  bibdate =      "Mon Jun 16 17:11:45 MDT 2008",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/talip.bib",
  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.",
  acknowledgement = ack-nhfb,
  articleno =    "9",
  fjournal =     "ACM Transactions on Asian Language Information
                 Processing",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?&idx=J820",
  keywords =     "language model; morphemes; perplexity; word error rate
                 and speech recognition",
}

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