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| Presentation | 2008-03-20 13:00 [Invited Talk] Feature Vector Classification based on Likelihood Ratio Jeong-sik Park, Sang-min Yoon, Yung-Hwan Oh (KAIST)  SP2007-187 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | This paper proposes a new feature vector classification method to reduce the recognition error due to overlap data in speaker or emotion recognition. The recognition process is composed of two distinct phases, training and test. During training phase, feature vectors are extracted from each speaker and emotion data and the respective speaker or emotion model (GMM) is constructed. In test phase, feature vector extracted from test utterance is applied to each model, and a model which has the maximum likelihood is decided as a result. The ideal training is constructing each model, minimizing overlap amongst models owing to several factors such as speaker or emotion similarities. Thus overlap disturbs classifying the GMMs and may degrade recognition accuracy. To reduce the effect of overlap, we classified feature vectors from training data into two categories, non-overlapped and overlapped, based on likelihood ratio. By using these separated feature vectors, we constructed a non-overlapped and an overlapped model, respectively, for each speaker and emotion. In test phase, we selected meaningful data from test utterance depending on likelihood ratio calculated from two kinds of models and used for decision-making. This method has an effect discarding overlap between models and thus improving recognition accuracy. We confirmed the efficiency of our method from speaker and emotion recognition experiments. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | / / / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 107, no. 551, SP2007-187, pp. 5-10, March 2008. | |
| Paper # | SP2007-187 | |
| Date of Issue | 2008-03-13 (SP) | |
| ISSN | Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | SP2007-187 |
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| Conference Information | |
| Committee | SP |
| Conference Date | 2008-03-20 - 2008-03-21 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Univ. Tokyo |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | International Workshop (Mar 20), Speech Production, Speech Perception, Hearing and Speech, etc. (Mar 21) |
| Paper Information | |
| Registration To | SP |
| Conference Code | 2008-03-SP |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Feature Vector Classification based on Likelihood Ratio |
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| 1st Author's Name | Jeong-sik Park |
| 1st Author's Affiliation | Korea Advanced Institute of Science and Technology (KAIST) |
| 2nd Author's Name | Sang-min Yoon |
| 2nd Author's Affiliation | Korea Advanced Institute of Science and Technology (KAIST) |
| 3rd Author's Name | Yung-Hwan Oh |
| 3rd Author's Affiliation | Korea Advanced Institute of Science and Technology (KAIST) |
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| Speaker | Author-3 |
| Date Time | 2008-03-20 13:00:00 |
| Presentation Time | 60 minutes |
| Registration for | SP |
| Paper # | SP2007-187 |
| Volume (vol) | vol.107 |
| Number (no) | no.551 |
| Page | pp.5-10 |
| #Pages | 6 |
| Date of Issue | 2008-03-13 (SP) |
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