trainModel.py 文件源码

def extract_features(file_name):
    X, sample_rate = librosa.load(file_name)
    stft = np.abs(librosa.stft(X))
    mfccs = np.array(librosa.feature.mfcc(y=X, sr=sample_rate, n_mfcc=8).T)
    chroma = np.array(librosa.feature.chroma_stft(S=stft, sr=sample_rate).T)
    mel = np.array(librosa.feature.melspectrogram(X, sr=sample_rate).T)
    contrast = np.array(librosa.feature.spectral_contrast(S=stft, sr=sample_rate).T)
    tonnetz = np.array(librosa.feature.tonnetz(y=librosa.effects.harmonic(X), sr=sample_rate).T)
    return mfccs,chroma,mel,contrast,tonnetz