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| Presentation | 2016-03-28 13:15 [Poster Presentation] An evaluation of acoustic-to-articulatory inversion mapping with latent trajectory Gaussian mixture model Patrick Lumban Tobing (NAIST), Tomoki Toda (Nagoya Univ./NAIST), Hirokazu Kameoka (NTT), Satoshi Nakamura (NAIST)  EA2015-85 SIP2015-134 SP2015-113 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this report, we present an evaluation of acoustic-to-articulatory inversion mapping based on latent trajectory Gaussian mixture model (LTGMM). In a conventional GMM-based inversion mapping system, GMM parameters are optimized by maximizing the likelihood of joint static and dynamic features of acoustic-articulatory data. In the mapping process, given the acoustic data, smoothly varying articulatory parameter trajectories are estimated by maximizing the conditional likelihood of their static features only, where the inter-frame correlation is taken into account by imposing the explicit relationship between static and dynamic features. Because training and optimization criteria are different from each other, the trained GMM is not optimum for the mapping process. A trajectory training method has been proposed to address this inconsistency problem [1]. However, this method has difficulties in optimization of some parameters, such as covariance matrices and a mixture component sequence. In this report, as another method to address the inconsistency problem, we propose an inversion mapping method based on latent trajectory GMM, inspired by the latent trjectory hidden Markov model [2]. The proposed method makes it possible to apply EM algorithm to model parameter optimization, which is difficult in the conventional trajectory training method. The experimental results demonstrate that the proposed LTGMM method outperforms the conventional GMM for the acoustic-to-articulatory inversion mapping task with lower values of root-mean-square error and higher values of correlation coefficient. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | acoustic-to-articulatory inversion mapping / Gaussian mixture model / trajectory training / inter-frame correlation / EM algorithm / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 115, no. 523, SP2015-113, pp. 111-116, March 2016. | |
| Paper # | SP2015-113 | |
| Date of Issue | 2016-03-21 (EA, SIP, 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 | EA2015-85 SIP2015-134 SP2015-113 |
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| Conference Information | |
| Committee | EA SP SIP |
| Conference Date | 2016-03-28 - 2016-03-29 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Beppu International Convention Center B-ConPlaza |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Engineering/Electro Acoustics, Speech, Signal Processing, and Related Topics |
| Paper Information | |
| Registration To | SP |
| Conference Code | 2016-03-EA-SP-SIP |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | An evaluation of acoustic-to-articulatory inversion mapping with latent trajectory Gaussian mixture model |
| Sub Title (in English) | |
| Keyword(1) | acoustic-to-articulatory inversion mapping |
| Keyword(2) | Gaussian mixture model |
| Keyword(3) | trajectory training |
| Keyword(4) | inter-frame correlation |
| Keyword(5) | EM algorithm |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Patrick Lumban Tobing |
| 1st Author's Affiliation | Nara Institute of Science and Technology (NAIST) |
| 2nd Author's Name | Tomoki Toda |
| 2nd Author's Affiliation | Nagoya University/Nara Institute of Science and Technology (Nagoya Univ./NAIST) |
| 3rd Author's Name | Hirokazu Kameoka |
| 3rd Author's Affiliation | Nippon Telegraph and Telephone Corporation (NTT) |
| 4th Author's Name | Satoshi Nakamura |
| 4th Author's Affiliation | Nara Institute of Science and Technology (NAIST) |
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| Speaker | Author-1 |
| Date Time | 2016-03-28 13:15:00 |
| Presentation Time | 90 minutes |
| Registration for | SP |
| Paper # | EA2015-85, SIP2015-134, SP2015-113 |
| Volume (vol) | vol.115 |
| Number (no) | no.521(EA), no.522(SIP), no.523(SP) |
| Page | pp.111-116 |
| #Pages | 6 |
| Date of Issue | 2016-03-21 (EA, SIP, SP) |
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