feature_extractor.py 文件源码

def log_power_spectrum_extractor(x, win_len, shift_len, win_type, is_log=False):
    samples = x.shape[0]
    frames = (samples - win_len) // shift_len
    stft = np.zeros((win_len, frames), dtype=np.complex64)
    spect = np.zeros((win_len // 2 + 1, frames), dtype=np.float64)

    if win_type == 'hanning':
        window = np.hanning(win_len)
    elif win_type == 'hamming':
        window = np.hamming(win_len)
    elif win_type == 'rectangle':
        window = np.ones(win_len)

    for i in range(frames):
        one_frame = x[i*shift_len: i*shift_len+win_len]
        windowed_frame = np.multiply(one_frame, window)
        stft[:, i] = np.fft.fft(windowed_frame, win_len)
        if is_log:
            spect[:, i] = np.log(np.power(np.abs(stft[0: win_len//2+1, i]), 2.))
        else:
            spect[:, i] = np.power(np.abs(stft[0: win_len//2+1, i]), 2.)

    return spect