Automatic speech segmentation for Chinese speech database based on HMM

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

  • JH Tao - , Tsinghua University (Autor:in)
  • HU Hain - , Siemens AG (Autor:in)

Abstract

The paper offers an optimized method in speech segmentation of Mandarin speech database by using Hidden Markov Model (HMM). The method takes the syllable boundaries into account. Testing shows that the accuracy of results is improved to 95% from 88% compared to the normal method. Especially, most of the boundaries between two vowels can also be well detected with the new method. The paper also analyzes the influence of the amount of HMM states and the amount of the training corpus.

Details

OriginalspracheEnglisch
Titel2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering. TENCOM '02. Proceedings
Redakteure/-innenBZ Yuan, XF Tang
Herausgeber (Verlag)Wiley-IEEE Press
Seiten481-484
Seitenumfang4
Band1
ISBN (Print)0-7803-7490-8
PublikationsstatusVeröffentlicht - 2002
Peer-Review-StatusJa
Extern publiziertJa

Konferenz

TitelIEEE Region 10 Technical Conference on Computers, Communications, Control and Power Engineering
KurztitelTENCOM 2002
Dauer28 - 31 Oktober 2002
StadtBeijing
LandChina

Externe IDs

Scopus 0038337070
ORCID /0000-0001-5973-5026/work/142253745

Schlagworte

Schlagwörter

  • speech segmentation, hidden Markov model