nasality.py 文件源码

def noise_removal(aud_sample):
    if (min(abs(aud_sample)) == 0):
      return aud_sample

    data = abs(np.copy(aud_sample))
    clf = KMeans(n_clusters = 2,n_init = 5)
    data = data.reshape(-1,1)
    clf.fit(data)
    if clf.cluster_centers_[0] < clf.cluster_centers_[1]:
      noise = 0
    else:
      noise = 1

    aud = np.copy(aud_sample)

    window = 500
    windowStride = 50
    for i in range(0,len(clf.labels_),windowStride):
        if sum(clf.labels_[i:i+window] == noise) == window:
            aud[i:i+window] = 0

    return aud