• DocumentCode
    394244
  • Title

    Microsoft Mulan - a bilingual TTS system

  • Author

    Chu, Min ; Peng, Hu ; Zhao, Yong ; Niu, Zhengyu ; Chang, Eric

  • Author_Institution
    Microsoft Res. Asia, Beijing, China
  • Volume
    1
  • fYear
    2003
  • fDate
    6-10 April 2003
  • Abstract
    This paper describes a bilingual text-to-speech (TTS) system, Microsoft Mulan, which switches between Mandarin and English smoothly and which maintains the sentence level intonation even for mixed-lingual texts. Mulan is constructed on the basis of the Soft Prediction Only prosodic strategy and the Prosodic-Constraint Orient unit-selection strategy. The unit-selection module of Mulan is shared across languages. It is insensitive to language identity, even though the syllable is used as the smallest unit in Mandarin, and the phoneme in English. Mulan has a unique module, the language-dispatching module, which dispatches texts to the language-specific front-ends and merges the outputs of the two front-ends together. The mixed texts are "uttered" out with the same voice. According to our informal listening test, the speech synthesized with Mulan sounds quite natural. Sample waves can be heard at: http://research.microsoft.com/-echang/proiects/tts/mulan.htm.
  • Keywords
    natural languages; speech synthesis; English; Mandarin; Microsoft Mulan; bilingual TTS system; bilingual text-to-speech system; informal listening test; language-dispatching module; language-specific front-ends; mixed texts; mixed-lingual texts; phoneme; prosodic-constraint orient unit-selection; sentence level intonation; soft prediction only prosodic strategy; syllable; unit-selection module; Acoustic testing; Asia; Electronic mail; Engines; Humans; Natural languages; Predictive models; Speech synthesis; Switches; Usability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-7663-3
  • Type

    conf

  • DOI
    10.1109/ICASSP.2003.1198768
  • Filename
    1198768