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P9: A Text-Independent Speaker Recognition System
Author: Catie Schwartz , Advisor: Ramani Duraiswami (CS)
Problem Statement Presentation
Project Proposal
Abstract
Speaker recognition is the computational task of validating a person’s identity based on their voice. The two phases of a speaker recognition system are the enrollment phase where speech samples from the different speakers are turned into models and the verification phase where a sample of speech is tested to determine if it matches a proposed speaker. In a text-independent system, there are no constraints in the words or phrases used during verification. Numerous approaches have been studied to make text-independent speaker recognition systems accurate with very short speech samples and robust against both channel variability (differences due to the medium used to record the speech) and speaker dependent variability (such as health or mood of the speaker). A text-independent speaker recognition system using Gaussian mixture models and factor analysis techniques will be implemented in Matlab and tested against the NIST SRE databases for validation.
MidYear Progress Report and
Presentation
Final Presentation ,
Final Report
