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Speaker recognition is the task of identifying a speaker using their voice. Speaker recognition is classified into two parts: speaker identification and speaker verification. While speaker identification is the process of determining which voice in a group of known voices best matches the speaker’, speaker verification is the task of accepting or rejecting the identity claim of a speaker by analyzing their acoustic samples. Speaker verification systems are computationally less complex than speaker identification systems since they require a comparison between only one or two models, whereas speaker identification requires comparison of one model to N speaker models.

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Speaker verification methods are divided into text-dependent and text-independent methods. In text-dependent methods, the speaker verification system has prior knowledge about the text to be spoken and the user is expected to speak this text. However, in a text-independent system, the system has no prior knowledge about the text to be spoken and the user is not expected to be cooperative. Text-dependent systems achieve high speaker verification performance from relatively short utterances, while text-independent systems require long utterances to train reliable models and achieve good performance.