generate_features.py 文件源码

def mean_variance_normalisation(h5f, mvn_h5f, vad=None):
    """Do mean variance normlization. Optionnaly use a vad.

    Parameters:
    ----------
    h5f: str. h5features file name
    mvn_h5f: str, h5features output name
    """
    dset = h5py.File(h5f).keys()[0]
    if vad is not None:
        raise NotImplementedError
    else:
        data = h5py.File(h5f)[dset]['features'][:]
        features = data
    epsilon = np.finfo(data.dtype).eps
    mean = np.mean(data)
    std = np.std(data)
    mvn_features = (features - mean) / (std + epsilon)
    shutil.copy(h5f, mvn_h5f)
    h5py.File(mvn_h5f)[dset]['features'][:] = mvn_features