Abstract
Support vector machines (SVM's) can be trained to classify manner transitions between phones and to identify the place of articulation of any given phone with high accuracy. The discriminant outputs of these SVM's can be used as input features for a standard ASR system. There is a significant improvement in correctness and accuracy using these SVM discriminant features when compared to an MFCC based recognizer of equal parameters.
Original language | English (US) |
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Pages | 697-700 |
Number of pages | 4 |
State | Published - 2005 |
Event | 9th European Conference on Speech Communication and Technology - Lisbon, Portugal Duration: Sep 4 2005 → Sep 8 2005 |
Other
Other | 9th European Conference on Speech Communication and Technology |
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Country/Territory | Portugal |
City | Lisbon |
Period | 9/4/05 → 9/8/05 |
ASJC Scopus subject areas
- General Engineering