s_left_2 = s_left_0(1+wid:end-wid) + s_left_1(1+4*wid:end-4*wid) * w_t; s_right_2 = s_right_0(1+wid:end-wid) + s_right_1(1+4*wid:end-4*wid) * w_t; s_left_2 = PixelShuffle(s_left_2,conv_t(6:21,:)); s_right_2 = PixelShuffle(s_right_2,conv_t(6:21,:));
时间: 2023-12-06 09:42:06 浏览: 79
这段代码看起来像是对音频信号进行一些处理,具体来说:
- `s_left_0` 和 `s_right_0` 是分别左右声道的原始音频信号;
- `s_left_1` 和 `s_right_1` 是左右声道的一次降采样后的信号;
- `wid` 是一个窗口大小,用于控制降采样的程度;
- `w_t` 是一个权重向量,用于加权平均左右声道的信号;
- `PixelShuffle` 是一个像素重排函数,用于将信号还原到原始采样率。
这段代码可能是在进行声音合成或者音频降噪等方面的应用。
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while(snr_t < 46 ) %迭代训练 s_left_0 = [fill,soud_left_d,fill]; s_right_0 = [fill,soud_right_d,fill]; s_left_1 = ResBlock(s_left_0,conv_t(2,:),conv_t(3,:)); s_right_1 = ResBlock(s_right_0,conv_t(2,:),conv_t(3,:)); s_left_1 = conv(s_left_1,conv_t(4,:)); s_right_1 = conv(s_right_1,conv_t(4,:)); s_left_2 = s_left_0(1+wid:end-wid) + s_left_1(1+4wid:end-4wid) * w_t; s_right_2 = s_right_0(1+wid:end-wid) + s_right_1(1+4wid:end-4wid) * w_t; s_left_2 = PixelShuffle(s_left_2,conv_t(6:21,:)); s_right_2 = PixelShuffle(s_right_2,conv_t(6:21,:)); s_left_2 = conv(s_left_2,conv_t(5,:)); s_right_2 = conv(s_right_2,conv_t(5,:)); s_left_2 = s_left_2(1+wid:end-wid); s_right_2 = s_right_2(1+wid:end-wid); power_s = Count(s_left_2(1,:)); power_mult = power_s / power_xr; s_left_2 = s_left_2 / (power_mult)^0.5; s_right_2 = s_right_2 / (power_mult)^0.5; temp = s_left_2 - soud_left_t; loss_num = LossCount(temp,soud_left); diff = Variance(temp,soud_left); snr = psnr(temp,soud_left);
这段代码的作用是对语音信号进行迭代训练和处理,希望获得更高的信噪比(SNR)。具体来说,它首先将输入的左右声道信号进行填充,然后通过ResBlock函数进行残差块的处理。接着,通过卷积操作对信号进行处理,并使用PixelShuffle函数对信号进行下采样。最后,通过计算信号的功率、多项式系数等参数,对信号进行归一化处理,并计算损失函数、方差和信噪比等指标。这个过程会不断迭代,直到信噪比达到指定的阈值。
while(snr_t < 46 ) %迭代训练 s_left_0 = [fill,soud_left_d,fill]; s_right_0 = [fill,soud_right_d,fill]; s_left_1 = ResBlock(s_left_0,conv_t(2,:),conv_t(3,:)); s_right_1 = ResBlock(s_right_0,conv_t(2,:),conv_t(3,:)); s_left_1 = conv(s_left_1,conv_t(4,:)); s_right_1 = conv(s_right_1,conv_t(4,:)); s_left_2 = s_left_0(1+wid:end-wid) + s_left_1(1+4*wid:end-4*wid) * w_t; s_right_2 = s_right_0(1+wid:end-wid) + s_right_1(1+4*wid:end-4*wid) * w_t; s_left_2 = PixelShuffle(s_left_2,conv_t(6:21,:)); s_right_2 = PixelShuffle(s_right_2,conv_t(6:21,:)); s_left_2 = conv(s_left_2,conv_t(5,:)); s_right_2 = conv(s_right_2,conv_t(5,:)); s_left_2 = s_left_2(1+wid:end-wid); s_right_2 = s_right_2(1+wid:end-wid); power_s = Count(s_left_2(1,:)); power_mult = power_s / power_xr; s_left_2 = s_left_2 / (power_mult)^0.5; s_right_2 = s_right_2 / (power_mult)^0.5; temp = s_left_2 - soud_left_t; loss_num = LossCount(temp,soud_left); diff = Variance(temp,soud_left); snr = psnr(temp,soud_left);
这段代码是一个音频处理的迭代训练过程。具体来说,它包括以下几个步骤:
1. 初始化输入信号,其中 soud_left_d 和 soud_right_d 是左右声道的音频数据;
2. 使用 ResBlock 函数对输入信号进行残差块处理;
3. 对处理后的信号进行卷积操作,并加上一个权重 w_t,得到 s_left_2 和 s_right_2;
4. 对 s_left_2 和 s_right_2 进行像素洗牌(PixelShuffle)操作;
5. 再次对洗牌后的信号进行卷积操作;
6. 对信号进行归一化处理,使得其功率与参考信号 power_xr 相同;
7. 计算残差和损失,以及信噪比(SNR)。
整个过程会不断迭代,直到 SNR 达到一定阈值(46)。这种音频处理技术可以用于语音增强、降噪等方面。