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Myanmar Number Normalization for Text-to-Speech

  • Aye Mya Hlaing
  • Win Pa Pa
  • Ye Kyaw Thu
Conference paper
Part of the Communications in Computer and Information Science book series (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.

Keywords

Myanmar number normalization Text normalization Weighted finite state transducer Myanmar text-to-speech Myanmar 

Notes

Acknowledgements

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

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Natural Language Processing LabUCSYYangonMyanmar
  2. 2.Artificial Intelligence LabOkayama Prefectural UniversityOkayamaJapan

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