An artificial Intelligence Approach to improving Speech Recognition

Master Thesis

2009

Permanent link to this Item
http://hdl.handle.net/11427/5180
Files
thesis_ebe_2009_lopes_lr.pdf (1.86 MB)
Authors
Lopes, Luis Ramos dos Santos
Supervisors
Mashao, Daniel
Ventura, Neco
Journal Title
Link to Journal
Journal ISSN
Volume Title
Publisher
Publisher

University of Cape Town

Department
Department of Electrical Engineering
Faculty
Faculty of Engineering and the Built Environment
License
Series
Abstract
Speech Recognition is a technology with promising applications. However, the performance of current speech recognizers greatly limit their widespread use. Approaches to reducing the word error rate have mainly been associated with statistical techniques. As a consequence, speech recognition results can still contain sentences that are nonsensical. The method proposed here, is to analize the output of any chosen speech recognition system, in order to determine whether a sentence contains syntactic or semantic errors. This is done via a software agent that uses the information from its knowledge base to attempt to correct the errors found. A system was implemented with a small vocabulary speaker-independent continuous speech recognition system, with limited sentence structures. The achieved increase in speech recognition accuracy, shows that there are bene ts in using this approach.
Description
Keywords
Engineering

Reference:

Lopes, L. 2009. An artificial Intelligence Approach to improving Speech Recognition. University of Cape Town.

Collections
Other Theses