Speaker recognition

Speaker Recognition

Speaker recognition is basically divided into two-classification: speaker recognition and speaker identification and it is the method of automatically identify who is speaking on the basis of individual information integrated in speech waves. Speaker recognition is widely applicable in use of speaker’s voice to verify their identity and control access to services such as banking by telephone, d...

Speaker Recognition

This chapter presents some of the main contributions in several topics of speaker recognition since 1978. Representative books and surveys on speaker recognition published during this period are listed. Theoretical models for automatic speaker recognition are contrasted with practical design methodology. Research contributions to measure process, feature extraction, and classification are selec...

Speaker recognition in a multi-speaker environment

We discuss the multi-speaker tasks of detection, tracking, and segmentation of speakers as included in recent NIST Speaker Recognition Evaluations. We consider how performance for the two-speaker detection task is related to that for the corresponding one-speaker task. We examine the effects of target speaker speech duration and the gender mix within test segments on results for these tasks. We...

Modeling intra-speaker variability for speaker recognition

In this paper we present a speaker recognition algorithm that models explicitly intra-speaker inter-session variability. Such variability may be caused by changing speaker characteristics (mood, fatigue, etc.), channel variability or noise variability. We define a session-space in which each session (either train or test session) is a vector. We then calculate a rotation of the session-space fo...

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words