Skip Navigation

IEICE Transactions on Information and Systems 2008 E91-D(3):393-401; doi:10.1093/ietisy/e91-d.3.393
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Request Permissions
Google Scholar
Right arrow Articles by ASANO, F.
Right arrow Search for Related Content
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Copyright © 2008 The Institute of Electronics, Information and Communication Engineers

Special Section on Robust Speech Processing in Realistic Environments -- Papers

Signal Processing Techniques for Robust Speech Recognition

Futoshi ASANO1

1 The author is with AIST, Tsukuba-shi, 305–8568 Japan. E-mail: f.asano{at}aist.go.jp


   Abstract

In this paper, signal processing techniques which can be applied to automatic speech recognition to improve its robustness are reviewed. The choice of signal processing techniques is strongly dependent on the scenario of the applications. The analysis of scenario and the choice of suitable signal processing techniques are shown through two examples.

Key Words: signal processing, automatic speech recognition, robustness


Manuscript received August 3, 2007. Manuscript revised September 28, 2007.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.