Automatic Lecture Transcription Based on Discriminative Data Selection for Lightly Supervised Acoustic Model Training-Reference-Cited by-同舟云学术

Automatic Lecture Transcription Based on Discriminative Data Selection for Lightly Supervised Acoustic Model Training

Published:2015 Issue:8 Volume:E98.D Page:1545-1552
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

LI Sheng¹,AKITA Yuya¹,KAWAHARA Tatsuya¹

Affiliation:

1. Graduate School of Informatics, Kyoto University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://www.jstage.jst.go.jp/article/transinf/E98.D/8/E98.D_2015EDP7047/_pdf

Reference29 articles.

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2. [2] H. Nanjo and T. Kawahara, “Language Model and Speaking Rate Adaptation for Spontaneous Presentation Speech Recognition,” IEEE-TSAP, vol.12, no.4, pp.391-400, 2004.

3. [3] I. Trancoso, R. Nunes, L. Neves, C. Viana, H. Moniz, D. Caseiro, and A.I. Mata, “Recognition of Classroom Lectures in European Portuguese,” Proc. INTERSPEECH, pp.281-284, 2006.

4. [4] J. Glass, T.J. Hazen, S. Cyphers, I. Malioutov, D. Huynh, and R. Barzilay, “Recent Progress in the MIT Spoken Lecture Processing Project,” Proc. INTERSPEECH, pp.2553-2556, 2007.

5. [5] H. Yamazaki, K. Iwano, K. Shinoda, S. Furui, and H. Yokota, “Dynamic Language Model Adaptation Using Presentation Slides for Lecture Speech Recognition,” Proc. INTERSPEECH, pp.2349-2352, 2007.

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