音声処理　TypeError: 'int' object is not subscriptable

音声処理のプログラムについて

以下の任意のSN比の音声ファイルを作成するプログラムの中で、snrの指定を0dBにした場合は実行できるのですが、それ以外の値(例：10dB, -5dBなど)を指定しようとすると、
[TypeError: 'int' object is not subscriptable]
とエラーが出てしまい実行できません。

どうしてでしょうか、ご存知の方ご教授いただけますと幸いです。

(ちなみにAnacondaを使用して実行しようとしています。)

python
1import argparse
2import array
3import math
4import numpy as np
5import random
6import wave
7
8
9def get_args():
10    parser = argparse.ArgumentParser()
11    parser.add_argument('--clean_file', type=str, required=True)
12    parser.add_argument('--noise_file', type=str, required=True)
13    parser.add_argument('--output_clean_file', type=str, default='')
14    parser.add_argument('--output_noise_file', type=str, default='')
15    parser.add_argument('--output_noisy_file', type=str, default='', required=True)
16    parser.add_argument('--snr', type=float, default='', required=True)
17
18    args = parser.parse_args(args=['--clean_file',"sample.wav", '--noise_file', "noise.wav", '--output_clean_file',"clear.wav",'--output_noise_file',"noise.wav",'--output_noisy_file',"noisy.wav",'--snr',0])
19    return args
20
21
22def cal_adjusted_rms(clean_rms, snr):
23    a = float(snr) / 20
24    noise_rms = clean_rms / (10**a) 
25    return noise_rms
26
27
28def cal_amp(wf):
29    buffer = wf.readframes(wf.getnframes())
30    amptitude = (np.frombuffer(buffer, dtype="int16")).astype(np.float64)
31    return amptitude
32
33
34def cal_rms(amp):
35    return np.sqrt(np.mean(np.square(amp), axis=-1))
36
37
38if __name__ == '__main__':
39    
40    args = get_args()
41    clean_file = args.clean_file
42    noise_file = args.noise_file
43    snr = args.snr
44    
45    clean_wav = wave.open(clean_file, "r")
46    noise_wav = wave.open(noise_file, "r")
47    
48    clean_amp = cal_amp(clean_wav)
49    noise_amp = cal_amp(noise_wav)
50    
51    start = random.randint(0, len(noise_amp)-len(clean_amp))
52    clean_rms = cal_rms(clean_amp)
53    split_noise_amp = noise_amp[start: start + len(clean_amp)]
54    noise_rms = cal_rms(split_noise_amp)
55    
56    adjusted_noise_rms = cal_adjusted_rms(clean_rms, snr)
57    
58    adjusted_noise_amp = split_noise_amp * (adjusted_noise_rms / noise_rms) 
59    mixed_amp = (clean_amp + adjusted_noise_amp)
60    
61    
62    if (mixed_amp.max(axis=0) > 32767): 
63        mixed_amp = mixed_amp * (32767/mixed_amp.max(axis=0))
64        clean_amp = clean_amp * (32767/mixed_amp.max(axis=0))
65        adjusted_noise_amp = adjusted_noise_amp * (32767/mixed_amp.max(axis=0))
66    
67    
68    noisy_wave = wave.Wave_write(args.output_noisy_file)
69    noisy_wave.setparams(clean_wav.getparams())
70    noisy_wave.writeframes(array.array('h', mixed_amp.astype(np.int16)).tostring() )
71    noisy_wave.close()
72    
73    
74    clean_wave = wave.Wave_write(args.output_clean_file)
75    clean_wave.setparams(clean_wav.getparams())
76    clean_wave.writeframes(array.array('h', clean_amp.astype(np.int16)).tostring() )
77    clean_wave.close()
78    
79    
80    noise_wave = wave.Wave_write(args.output_noise_file)
81    noise_wave.setparams(clean_wav.getparams())
82    noise_wave.writeframes(array.array('h', adjusted_noise_amp.astype(np.int16)).tostring() )
83    noise_wave.close()