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International Conference of the Pacific Association for Computational Linguistics

PACLING 2017: Computational Linguistics pp 263–274Cite as

Myanmar Number Normalization for Text-to-Speech

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 781))

Abstract

Text Normalization is an essential module for Text-to-Speech (TTS) system as TTS systems need to work on real text. This paper describes Myanmar number normalization designed for Myanmar Text-to-Speech system. Semiotic classes for Myanmar language are identified by the study of Myanmar text corpus and Weighted Finite State Transducers (WFST) based Myanmar number normalization is implemented. Number suffixes and prefixes are also applied for token classification and finally, post-processing has been done for tokens that cannot be classified. This approach achieves average tag accuracy of 93.5% for classification phase and average Word Error Rate (WER) 0.95% for overall performance which is 5.65% lower than rule-based system. The results show that this approach can be used in Myanmar TTS system, and to our knowledge, this is the first published work of Myanmar number normalization system designed for Myanmar TTS system.

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Notes

  1. 1.

    http://www2.nict.go.jp/astrec-att/member/mutiyama/ALT/index.html.

  2. 2.

    http://www.openfst.org/twiki/bin/view/GRM/Thrax.

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Acknowledgements

This work is partly supported by the ASEAN IVO project “Open Collaboration for Developing and Using Asian Language Treebank”.

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Authors and Affiliations

  1. Natural Language Processing Lab, UCSY, Yangon, Myanmar

    Aye Mya Hlaing & Win Pa Pa

  2. Artificial Intelligence Lab, Okayama Prefectural University, Okayama, Japan

    Ye Kyaw Thu

Authors
  1. Aye Mya Hlaing
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  2. Win Pa Pa
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  3. Ye Kyaw Thu
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Corresponding author

Correspondence to Aye Mya Hlaing .

Editor information

Editors and Affiliations

  1. Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan

    Kôiti Hasida

  2. Natural Language Processing Lab, University of Computer Studies, Yangon, Yangon, Myanmar

    Win Pa Pa

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Hlaing, A.M., Pa, W.P., Thu, Y.K. (2018). Myanmar Number Normalization for Text-to-Speech. In: Hasida, K., Pa, W. (eds) Computational Linguistics. PACLING 2017. Communications in Computer and Information Science, vol 781. Springer, Singapore. https://doi.org/10.1007/978-981-10-8438-6_21

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  • DOI: https://doi.org/10.1007/978-981-10-8438-6_21

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8437-9

  • Online ISBN: 978-981-10-8438-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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