Abstract
An essential element of any speech recognition system is the language model. A language model attempts to identify and make use of the regularities in natural language to better define language syntax for easier recognition. One major obstacle in speech recognition is the variability and uncertainty of message content. This coupled with inherent noise distortion and losses that occur in speech emphasize the need for a good language model. This paper describes the work done in generation of language model for Tamil speech recognition system. From the study the performance of Morpheme based Language model is better compared to other models tried for Tamil speech recognizer.
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Saraswathi, S., Geetha, T.V. (2004). Building Language Models for Tamil Speech Recognition System. In: Manandhar, S., Austin, J., Desai, U., Oyanagi, Y., Talukder, A.K. (eds) Applied Computing. AACC 2004. Lecture Notes in Computer Science, vol 3285. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30176-9_21
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DOI: https://doi.org/10.1007/978-3-540-30176-9_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23659-7
Online ISBN: 978-3-540-30176-9
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