Improving the Readability of ASR Results for Lectures Using Multiple Hypotheses and Sentence-Level Knowledge-Reference-Cited by-同舟云学术

Improving the Readability of ASR Results for Lectures Using Multiple Hypotheses and Sentence-Level Knowledge

Published:2012 Issue:4 Volume:E95.D Page:1101-1111
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

FUJII Yasuhisa¹,YAMAMOTO Kazumasa¹,NAKAGAWA Seiichi¹

Affiliation:

1. Department of Information and Computer Sciences Toyohashi University of Technology

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/E95.D/4/E95.D_4_1101/_pdf

Reference30 articles.

1. [1] Y. Fujii, K. Yamamoto, N. Kitaoka, and S. Nakagawa, “Class lecture summarization taking into account consectiveness of important sentences,” Proc. Interspeech, pp.2438-2441, Sept. 2008.

2. [2] C. Chelba and A. Acero, “Indexing uncertainty for spoken document search,” Proc. Interspeech, pp.61-64, Sept. 2005.

3. [3] S. Togashi and S. Nakagawa, “A browsing system for classroom lecture speech,” Proc. Interspeech, pp.2803-2806, Sept. 2008.

4. [4] J. Glass, S.C.T.J. Hazen, I. Malioutov, D. Huynh, and R. Barzilay, “Recent progress in the MIT spoken lecture processing project,” Proc. Interspeech, pp.2553-2356, Aug. 2007.

5. [5] S. Kogure, H. Nishizaki, M. Tsuchiya, K. Yamamoto, S. Togashi, and S. Nakagawa, “Speech recognition performance of CJLC: Corpus of Japanese lecture contents,” Proc. Interspeech, pp.1554-1557, Sept. 2008.

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Exploration of Automatic Speech Recognition for Deaf and Hard of Hearing Students in Higher Education Classes;The 21st International ACM SIGACCESS Conference on Computers and Accessibility;2019-10-24

2. Safety First: Conversational Agents for Health Care;Human–Computer Interaction Series;2018