Development of a Taiwanese Speech Synthesis System Using Hidden Markov Models and a Robust Tonal Phoneme Corpus

Yung Ji Sher, Ming Chun Hsu, Yu-Hsien Chiu, Yeou Jiunn Chen, Chung Hsien Wu, Jiunn Liang Wu

研究成果: Article同行評審


The number of young native speakers of Taiwanese, the variant of Southern Min spoken in Taiwan, has decreased. Technological advancements such as text-to-speech (TTS) systems could help arrest this decline. The aim of this study was to design a robust tonal phoneme corpus and a speech synthesis system for Modern Literal Taiwanese (MLT). MLT subsyllables were analyzed using phonetics and phonology to establish tonal phoneme models. These robust tonal phoneme models and hidden Markov models were used to construct an MLT TTS synthesis system. Algorithm-based training resulted in 869 balanced sentences containing 12,544 syllables, with each sentence containing an average of 14.4 syllables. In total, 218 sentences, which included rare phonemes, were manually drafted to supplement the corpus. The synthesized phonemes were deemed to have high intelligibility and could be included in the developed TTS system. According to the HTK speech recognition tool, the overall phoneme recognition rate was 96.47%. Testers, who were native Taiwanese speakers, assigned the synthesized sentences a mean opinion score of 4, indicating that they sounded natural. This developed system and the results described herein can inspire future developments in speech technology and computational linguistics.

頁(從 - 到)283-302
期刊Journal of Information Science and Engineering
出版狀態Published - 2024 3月

All Science Journal Classification (ASJC) codes

  • 軟體
  • 人機介面
  • 硬體和架構
  • 圖書館與資訊科學
  • 計算機理論與數學


深入研究「Development of a Taiwanese Speech Synthesis System Using Hidden Markov Models and a Robust Tonal Phoneme Corpus」主題。共同形成了獨特的指紋。