写一段完整的matlab代码，提取语音信号的mfcc特征（语音信号存储在audio_data中）

% 导入语音信号数据
load('audio_data.mat');

% 设定参数
fs = 8000; % 采样率
winlen = 0.025; % 窗长
hoplen = 0.01; % 帧移
nfft = 256; % FFT点数
numcep = 13; % MFCC系数数目
lifter = 22; % 倒谱提升系数

% 对语音信号进行预处理
audio_data = audio_data / max(abs(audio_data)); % 归一化
audio_data = filter([1 -0.97], 1, audio_data); % 预加重

% 分帧
frame_len = round(winlen*fs);
frame_hop = round(hoplen*fs);
frames_num = floor((length(audio_data)-frame_len)/frame_hop) + 1;
frames = zeros(frame_len,frames_num);
for i = 1:frames_num
start_index = (i-1)*frame_hop + 1;
end_index = start_index + frame_len - 1;
frames(:,i) = audio_data(start_index:end_index);
end

% 加窗
window = hamming(frame_len);
frames = frames .* repmat(window,1,frames_num);

% 计算功率谱
mag_frames = abs(fft(frames,nfft));
pow_frames = (1/nfft) * (mag_frames.^2);

% 建立Mel滤波器组
low_freq_mel = 0;
high_freq_mel = 2595*log10(1+(fs/2)/700);
mel_points = linspace(low_freq_mel,high_freq_mel,23);
hz_points = 700*(10.^(mel_points/2595)-1);
bin = floor((nfft+1)*hz_points/fs);

filter_bank = zeros(numcep,nfft/2+1);
for j = 1:numcep
for i = 1:(bin(j+1)-bin(j))
filter_bank(j,bin(j)+i) = (i-1)/(bin(j+1)-bin(j));
end
for i = (bin(j+1)-bin(j)+1):(bin(j+2)-bin(j+1))
filter_bank(j,bin(j)+i) = (bin(j+2)-i)/(bin(j+2)-bin(j+1));
end
end

% 计算MFCC系数
mel_energies = filter_bank * pow_frames(1:nfft/2+1,:);
log_mel_energies = log10(mel_energies + eps);
mfcc_coeffs = dct(log_mel_energies);

% 提升MFCC系数
cep_lifter = (1:numcep)';
cep_lifter = 1 + (lifter/2)*sin(pi*cep_lifter/lifter);
mfcc_coeffs = mfcc_coeffs .* repmat(cep_lifter,1,frames_num);

% 取前13个MFCC系数
mfcc_coeffs = mfcc_coeffs(1:numcep,:);

% 显示MFCC系数
disp(mfcc_coeffs);