Speaker Recognition Based on Neural Networks Speaker Recognition Based on Neural Networks lets you to identify people using the acoustic features of speech
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Speaker Recognition Based on Neural Networks Description

Text-independent speaker recognition based on Neural Networks Matlab source code. Speaker recognition or voice recognition is the task of recognizing people from their voices. Such systems extract features from speech, model them and use them to recognize the person from his/her voice. Speaker recognition has a history dating back some four decades, where the output of several analog filters was averaged over time for matching. Speaker recognition uses the acoustic features of speech that have been found to differ between individuals. These acoustic patterns reflect both anatomy (e.g., size and shape of the throat and mouth) and learned behavioral patterns (e.g., voice pitch, speaking style). This incorporation of learned patterns into the voice templates (called voiceprints) has earned speaker recognition its classification as a behavioral biometric. Version 1.1 may include unspecified updates, enhancements, or bug fixes.

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