simple-generative-model.py 文件源码

def get_audio_from_model(model, sr, duration, seed_audio):
    print 'Generating audio...'
    new_audio = np.zeros((sr * duration))
    curr_sample_idx = 0
    while curr_sample_idx < new_audio.shape[0]:
        distribution = np.array(model.predict(seed_audio.reshape(1,
                                                                 frame_size, 1)
                                             ), dtype=float).reshape(256)
        distribution /= distribution.sum().astype(float)
        predicted_val = np.random.choice(range(256), p=distribution)
        ampl_val_8 = ((((predicted_val) / 255.0) - 0.5) * 2.0)
        ampl_val_16 = (np.sign(ampl_val_8) * (1/256.0) * ((1 + 256.0)**abs(
            ampl_val_8) - 1)) * 2**15
        new_audio[curr_sample_idx] = ampl_val_16
        seed_audio[-1] = ampl_val_16
        seed_audio[:-1] = seed_audio[1:]
        pc_str = str(round(100*curr_sample_idx/float(new_audio.shape[0]), 2))
        sys.stdout.write('Percent complete: ' + pc_str + '\r')
        sys.stdout.flush()
        curr_sample_idx += 1
    print 'Audio generated.'
    return new_audio.astype(np.int16)