By Topic

Endpoint detection based on mel-scale features and phoneme segmentation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Ding Hao ; Dept. of Electron. & Inf. Eng., Huazhong Univ. of Sci. & Technol., China ; Yao Tianren

The conventional methods for speech endpoint detection based on some simple features such as energy and zero-crossing cannot obtain precise results. The proposed method in this paper is based on combination of Mel-scale features with phoneme segmentation. The experiments show that the high accurate detection can be obtained. In addition, the detector cannot only segment vowel and consonant, but also consonants itself. It can help further to reduce recognition error in speech recognition.

Published in:

Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on  (Volume:1 )

Date of Conference:

31 Aug.-4 Sept. 2004