写一段MATLAB中计算语音增强前后的信噪比生成增强后的语音文件分析处理效果。代码

% 读取语音信号 [x, fs] = audioread('speech.wav');

% 添加噪声 noise = randn(size(x)); SNR = 5; % 信噪比为5dB noise = noise * sqrt(var(x)/var(noise)/10^(SNR/10)); y = x + noise;

% 语音增强 y_enhanced = enhance_speech(y);

% 计算信噪比 SNR_before = 10log10(sum(x.^2)/sum(noise.^2)); SNR_after = 10log10(sum(x.^2)/sum((y_enhanced-x).^2)); fprintf('信噪比（增强前）：%0.2f dB\n', SNR_before); fprintf('信噪比（增强后）：%0.2f dB\n', SNR_after);

% 生成增强后的语音文件 audiowrite('speech_enhanced.wav', y_enhanced, fs);

% 分析处理效果 subplot(3,1,1); plot(x); title('原始语音'); subplot(3,1,2); plot(y); title('加噪语音'); subplot(3,1,3); plot(y_enhanced); title('增强后语音');

function y_enhanced = enhance_speech(y) % 语音增强函数 % y: 加噪语音信号 % y_enhanced: 增强后语音信号

% 预处理 frame_length = 20; % 帧长为20ms frame_shift = 10; % 帧移为10ms frame_size = round(frame_length/1000fs); frame_step = round(frame_shift/1000fs);

% 分帧 frames = buffer(y, frame_size, frame_size-frame_step); frames = frames(:, 1:end-1); % 去掉最后一帧

% 计算短时功率谱 win = hamming(frame_size); power_frames = abs(fft(frames.*win)).^2; power_frames = power_frames(1:frame_size/2+1, :);

% 估计噪声功率谱 noise_frames = power_frames(:, power_frames(1,:) < mean(power_frames(1,:)));

% 计算噪声功率谱 noise_power = mean(noise_frames, 2);

% 噪声门限 alpha = 3;

% 计算增强后的功率谱 enhanced_power_frames = power_frames - alpha*noise_power;

% 去除负值 enhanced_power_frames(enhanced_power_frames < 0) = 0;

% 重构语音信号 enhanced_frames = real(ifft(sqrt(enhanced_power_frames).exp(1iangle(fft(frames))))); y_enhanced = overlap_add(enhanced_frames, frame_step);

end

function y = overlap_add(frames, frame_step) % 重叠相加法 % frames: 分帧后的信号 % frame_step: 帧移

[n_frame, frame_size] = size(frames); y = zeros((n_frame-1)*frame_step+frame_size, 1);

for i = 1:n_frame start_idx = (i-1)*frame_step+1; end_idx = start_idx+frame_size-1; y(start_idx:end_idx) = y(start_idx:end_idx) + frames(i,:)'; end

en