Abstract
We present the concept of a scaled random segmental model, which aims to overcome the modeling problem created by the fact that segment realizations of the same phonetic unit differ in length. In the scaled model the variance of the random mean trajectory is inversely proportional to the segment length. The scaled model enables a Baum-Welch type parameter reestimation, unlike the previously suggested, non-scaled models, that require more complicated iterative estimation procedures. In experiments we have conducted with phoneme classification, it was found that the scaled model shows improved performance compared to the non-scaled model.
Original language | English |
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Title of host publication | Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998 |
Pages | 809-812 |
Number of pages | 4 |
DOIs | |
State | Published - 1998 |
Externally published | Yes |
Event | 1998 23rd IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998 - Seattle, WA, United States Duration: 12 May 1998 → 15 May 1998 |
Publication series
Name | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
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Volume | 2 |
ISSN (Print) | 1520-6149 |
Conference
Conference | 1998 23rd IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998 |
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Country/Territory | United States |
City | Seattle, WA |
Period | 12/05/98 → 15/05/98 |
Bibliographical note
Funding Information:The Abhishek Upadhyay is thankful University Grant Commission (UGC) for providing fellowship for pursuing this work respectively.
Funding
The Abhishek Upadhyay is thankful University Grant Commission (UGC) for providing fellowship for pursuing this work respectively.
Funders | Funder number |
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University Grants Commission |