Linear trajectory models incorporating preprocessing parameters

Details Linear trajectory models incorporating preprocessing parameters Linear trajectory models incorporating preprocessing parameters

1998-03-02

2000-06-13

Hudspeth, David R.

Data processing: speech signal processing, linguistics, language

Speech signal processing

Recognition

704243, 704202, 704201, G10L 1514

Patent

active

060760583

ABSTRACT:
The proposed model aims at finding an optimal linear transformation on the Mel-warped DFT features according to the minimum classification error (MCE) criterion. This linear transformation, along with the (NSHMM) parameters, are automatically trained using the gradient descent method. An advantageous error rate reduction can be realized on a standard 39-class TIMIT phone classification task in comparison with the MCE-trained NSHMM using conventional preprocessing techniques.

REFERENCES:
patent: 5579436 (1996-11-01), Chou et al.
patent: 5606644 (1997-02-01), Chou et al.
patent: 5794194 (1998-08-01), Takebayashi et al.
patent: 5835890 (1998-11-01), Matsui et al.
"HMM based S.R using state . . . on mel-warped DFT features" Chengalvarayan IEEE pp. 243-255, May 1997.
Matsui et al. "a study of speaker adaptation based on minimum classification error training", 1995.
Rathinavelu et al. "the trended HMM with discrinative training for phonetic classification", Oct. 1996.
Takahashi et al. "Minimum classification error training for a small amount of data enhanced by vector field-smoothed bayesian learning", Mar. 1996.

Affiliated with

Also associated with

Rating

Linear trajectory models incorporating preprocessing parameters does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Linear trajectory models incorporating preprocessing parameters , we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Linear trajectory models incorporating preprocessing parameters will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-2078114