Used Speaker Recognition Based on Neural Networks for Windows?


Editors’ Review

Download.com staff
This Matlab source code enables text-independent speaker recognition using neural networks. It analyzes acoustic speech features to identify individuals based on their unique voices.
  • Pros

    • Uses neural networks for speaker recognition
    • Text-independent recognition capability
    • Leverages acoustic speech features
    • Provides Matlab source code
    • Based on voiceprints and behavioral biometrics
  • Cons

    • Details of version 1.1 updates are unspecified
    • Specific algorithms and network architectures not detailed

Used Speaker Recognition Based on Neural Networks for Windows?


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Full Specifications

GENERAL
Release
Latest update
Version
1.1
OPERATING SYSTEMS
Platform
Windows
Operating System
  • Windows XP
  • Windows 2000
  • Windows 10
  • Windows NT
  • Windows 98
  • Windows ME
  • Windows 95
  • Windows 3
Additional Requirements
Windows 3.x/95/98/Me/NT/2000/XP, Matlab Signal Processing and Neural Net. Toolboxes
POPULARITY
Total Downloads
3,741
Downloads Last Week
0

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Developer’s Description

Identify people using the acoustic features of speech.

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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