ragibson/MFCC-speech-recognition
Real-time speech recognition via "Mel-Frequency Cepstral Coefficients" neural networks.
This project helps you build a system that can quickly understand spoken commands, even on simple computers. It takes short audio clips as input and tells you what command was spoken, allowing anyone to integrate voice control into their applications or devices without needing powerful hardware.
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Use this if you need to implement highly responsive, real-time voice command recognition on devices with limited processing power.
Not ideal if you need to transcribe long conversations or perform general speech-to-text conversion rather than discrete command recognition.
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Jupyter Notebook
License
MIT
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Last pushed
May 23, 2019
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