Scheduled System Maintenance on May 29th, 2015:
IEEE Xplore will be upgraded between 11:00 AM and 10:00 PM EDT. During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

An information gain and grammar complexity based approach to attribute selection in speech enabled information retrieval dialogs

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Haiping Li ; IBM China Res. Lab, Beijing, China ; Haixin Chai

An effective dialog driven method is required for today's speech enabled information retrieval systems, such as name dialers. Similar to the dynamic sales dialog for electronic commerce scenarios, information gain measure based approaches are widely used for attribute selection and dialog length reduction. However, for speech enabled information retrieval systems, another important factor influencing attribute selection is speech recognition accuracy. Too low accuracy results in a failed dialog. Recognition accuracy varies with many issues, including acoustic model performance and grammar complexity. The acoustic model is fixed for a whole dialog, while grammar is different for each interaction round, thereby grammar complexity influences the attribute selected for the next question. An approach combining both information gain measurement and grammar complexity is presented for a dynamic dialog driven system. Offline evaluations show that this approach can give a trade-off between the target of faster discrimination of the candidates for retrieval and higher recognition accuracy.

Published in:

Chinese Spoken Language Processing, 2004 International Symposium on

Date of Conference:

15-18 Dec. 2004