帮我写一段代码在matlab软件中基于倒谱法实现语音信号的共振峰提取

下面是一个基于倒谱法实现语音信号的共振峰提取的示例代码：

% 读取语音信号并进行预处理 [x, Fs] = audioread('speech.wav'); x = x(:, 1); % 取单声道信号 x = x - mean(x); % 去除直流分量 x = x / max(abs(x)); % 幅值归一化

% 分帧并进行加窗 frame_len = round(20 * Fs / 1000); % 帧长为20ms frame_shift = round(10 * Fs / 1000); % 帧移为10ms num_frames = floor((length(x) - frame_len) / frame_shift) + 1; % 总帧数 frames = zeros(frame_len, num_frames); for i = 1:num_frames start_idx = (i - 1) * frame_shift + 1; end_idx = start_idx + frame_len - 1; frames(:, i) = x(start_idx:end_idx) .* hamming(frame_len); end

% 计算每帧的倒谱系数 lpc_order = 12; % LPC阶数为12 a = zeros(lpc_order + 1, num_frames); for i = 1:num_frames a(:, i) = lpc(frames(:, i), lpc_order); end cepstrum = real(ifft(log(abs(a)))); % 倒谱系数

% 计算共振峰频率和带宽 freqs = zeros(lpc_order, num_frames); bandwidths = zeros(lpc_order, num_frames); for i = 1:num_frames r = cepstrum(:, i); r(1) = 0; % 去除直流分量 for j = 2:lpc_order+1 r(j) = r(j) + r(lpc_order+2-j); end r = r(1:lpc_order+1); [a, freqs(:, i)] = findpeaks(r, 'SortStr', 'descend', 'NPeaks', lpc_order); for j = 1:lpc_order idx = find(r > a(j) / 2, 1, 'first'); if isempty(idx) idx = lpc_order + 1; end bandwidths(j, i) = (idx - freqs(j, i)) / (2 * pi); end end

% 绘制共振峰频率和带宽随时间的变化 t = (0:num_frames-1) * frame_shift / Fs; figure; subplot(2, 1, 1); plot(t, freqs); xlabel('Time (s)'); ylabel('Frequency (Hz)'); title('Formant Frequencies'); legend('F1', 'F2', 'F3', 'F4', 'F5', 'F6'); subplot(2, 1, 2); plot(t, bandwidths); xlabel('Time (s)'); ylabel('Bandwidth (Hz)'); title('Formant Bandwidths'); legend('F1', 'F2', 'F3', 'F4', 'F5', 'F6');