第5章前半を追加#72
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q02だけ確認が必要かもです |
i14kwmr
reviewed
Aug 8, 2023
| plt.plot(np.arange(0, sec * y.shape[0]) / fs, y) | ||
| plt.plot(np.arange(0, sec * y.shape[0]) / fs, x1_pad) | ||
| plt.xlim(0.02, 0.04) | ||
| plt.savefig("q07.pdf") |
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以下のコードを記述するとSNRの比較ができます！参考までに
S1 = my_stft(L, S, s, win)
_x1 = my_istft(S, X1, win)
_s1 = my_istft(S, S1, win)
print("input SNR:", 10 * np.log10(np.sum(_s1 ** 2) / np.sum((_x1 - _s1) ** 2))) # input SNR: 9.95
print("output SNR:", 10 * np.log10(np.sum(_s1 ** 2) / np.sum((y - _s1) ** 2))) # output SNR: 14.51
i14kwmr
reviewed
Aug 8, 2023
| F = L // 2 + 1 | ||
| fs = 16000 | ||
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| d_list = [2, 5, 10] # マイク間隔 |
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コメント：
単位はmとなっているので、意図する2 [cm], 5 [cm], 10 [cm]とはなっていないことに注意です
i14kwmr
reviewed
Aug 8, 2023
| w = np.empty([F, 360, M], dtype="complex") | ||
| for f in range(0, F): | ||
| for theta in range(0, 360): | ||
| w[f, theta, :] = q01.linear_array_vector(0.05, M, theta, f) |
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コメント：
q01.linear_array_vector(0.05, M, theta, f)の引数fは周波数を想定しているのに対し、32行目では周波数インデックスを渡しています
def linear_array_vector(d, M, theta, f):
"""直線状アレイのアレイマニフォールドベクトルを求める
Args:
d (double): アレイ間隔
M (int): マイク数
theta (int): 音源方向（y軸から反時計回りが正の向き）
f (int): 周波数
Return:
amv: アレイマニフォールドベクトル
"""
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コメント：
ビームフォーマの式は正しくは
w[f, theta, :] = w[f, theta, :] / (w[f, theta, :].conjugate() @ w[f, theta, :])
Contributor
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第5章前半 q02について 変更確認しました okです！ |
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実行結果
q01.py
[0.7868537-0.61713958j 1. +0.j 0.7868537+0.61713958j]
q02.py
[0.7868537 -0.61713958j 0.6148926 +0.78861086j 0.97051349-0.2410468j ]
q04.py
[[[1. +0.j 1.25+0.j]
[1.25+0.j 5.25+0.j]]
[[4. +0.j 1.5 +0.j]
[1.5 +0.j 1.25+0.j]]
[[9. +0.j 0.75+0.j]
[0.75+0.j 0.75+0.j]]]