Sixth International Conference on Spoken Language Processing
October 16-20, 2000
Using GMM for Voiced/Voiceless Segmentation and Tone Decision in Mandarin Continuous Speech Recognition
Ching X. Xu
Northwestern University, Evanston, IL 60208, USA
In this paper, methods of Gaussian Mixture Model (GMM) are
presented for both silence/voiced/voiceless segmentation and
tone decision in Mandarin continuous speech recognition system.
GMM has been used for silence/voiced/voiceless segmentation
before, but the feature parameters can be modified to improve
both accuracy and speed. As a popular method in pattern
recognition, GMM is first proposed for tone decision. The two
GMMs used are proved to be capable and potential.
Xu, Ching X. (2000):
"Using GMM for voiced/voiceless segmentation and tone decision in Mandarin continuous speech recognition",
In ICSLP-2000, vol.2, 975-978.