Concatenated phoneme models for text-variable speaker recognition

Abstract

Methods that create models to specify both speaker and phonetic information accurately by using only a small amount of training data for each speaker are investigated. For a text-dependent speaker recognition method, in which arbitrary key texts are prompted from the recognizer, speaker-specific phoneme models are necessary to identify the key text and recognize the speaker. Two methods of making speaker-specific phoneme models are discussed: phoneme-adaptation of a phoneme-independent speaker model and speaker-adaptation of universal phoneme models. The authors also investigate supplementing these methods by adding a phoneme-independent speaker model to make up for the lack of speaker information. This combination achieves a rejection rate as high as 98.5% for speech that differs from the key text and a speaker verification rate of 100.0%.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>