Abstract
For communication, speech is one of the natural forms. A person’s voice contains various parameters that convey information such as emotions, gender, attitude, health, and identity. Determination of these parameters will help to further develop the technology into a reliable and consistent means of identification using speaker recognition. Speaker recognition technologies have wide application areas especially in authentication; surveillance and forensic speaker recognition. In addition, speaker recognition refers to the automated method of identifying or confirming the identity of an individual based on his/her voice. Speech recognition strips out the personal differences to detect the words. Speaker recognition typically disregards the language and meaning to detect the physical person behind the speech. Speech recognition is language-dependent, while Speaker recognition is independent of language. In essence, voice biometrics provides speaker recognition rather than speech recognition. The most accepted form of identification for a human is his/her speech signal. Principally the speaker recognition is the computing task of validating a user’s claimed identity 108using characteristics extracted from their voice. The speaker recognition process based on a speech signal is treated as one of the most exciting technologies of human recognition. For Speaker identification activities we mainly emphasize the physical features of signal. Speakers could be categorized as speaker identification and speaker verification. In speaker identification, the obtained features are compared with all the speaker’s features which are stored in a voice model database and in speaker verification the obtained features are only compared with the stored features of the speaker he/she claimed to be. In this chapter the general principles of speaker recognition, methodology, and applications are discussed.
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