An algorithm for characterizing context-governed speech production patterns

Speech recognition and analysis can be improved by using methods that can effectively characterize important speech patterns of a speaker without requiring hours of data. This thesis defines a method by which key contexts related to systematic speech modification can be used to create a profile of the speech produced by a speaker. Using acoustic and prosodic information, contexts that create the potential for speech modifications can be specified. Then, by filtering speech produced by a speaker in the targeted contexts, the patterns of speech production in these contexts can be characterized. With these productions, likely underlying contexts that are associated with the productions can be used to enhance speech recognition when these contexts arise in new speech.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2023

Author dc:creator

• Torres, Deborah Cheron

Advisor dc:contributor.advisor

• Shattuck-Hufnagel, Stefanie

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/151438

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/151438