Latent Semantic Analysis for Speaker Recognition

摘要

There exists certain traits specific to a speaker that help in easy identification of the speaker among a familiar set of speakers. These include certain dis-fluencies, and mannerisms like stress for certain words, frequent usage of certain phrases, manner of pronunciation and back channels. The focus of this paper is identification of a speaker using such idiolectic traits in conversational speech. Every normal conversation by a speaker contains his idiolectic signature. A model is developed in the latent semantic analysis framework to capture this signature. The similarity of the idiolectic signature in the test utterance to that captured by the model is used to hypothesise the target speaker. The technique is demonstrated for the NIST 2003 extended data task.