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Speech Feature Extraction

The repository describes the feature extraction methods for speech signals.

Free speech datasets

  • OpenLSR: OpenSLR is a site devoted to hosting speech and language resources, such as training corpora for speech recognition, and software related to speech recognition.
  • VoxForge: VoxForge is now mirroring the LT and the Teleccoperation group Open Speech Data Corpus for German with 35 hours of speech from about 180 speakers.
  • TIMIT: The DARPA TIMIT Acoustic-Phonetic Continuous Speech Corpus.
  • Mozilla Speech: Mozilla Releases the world's Second Largest Public Voice Data Set on Nov 29th, 2017.
  • Open Data for Deep Learning

File description

  • feature_extraction_functions.py: a set of feature extraction functions from RDShi-SpeakerCount.
  • MFCC: Mel-frequency cepstral coefficients calculation.
    • MFCC.py, MFCCTest.py: Compute the MFCC feature.
    • FeatureExtraction.ipynb: Speech preprocessing, including loading data, pre-emphasis, framing, window, Fourier-transform, power spectrum, filter banks, mfccs and mean normalization.
  • Volume: volume calculation.
  • ZeroCR: Zero-Crossing Rate calculation.
  • Pitch: Pitch calculation and pitch tracking.
  • Timbre: spectrogram drawing.
  • VAD: EPD (End-Point Detection), or Speech Detection, or VAD(Voice Activity Detection).

Requirements

Anaconda3 (Python3.x)

References & Code source