基于matlab的语音识别实现倒谱分析代码

以下是基于matlab的语音识别实现倒谱分析的代码：

% 读取音频文件
[x, fs] = audioread('audio.wav');

% 分帧
frame_length = 0.025; % 每帧长度为25ms
frame_shift = 0.01; % 帧移为10ms
frame_size = frame_length * fs;
frame_shift_size = frame_shift * fs;
frame_num = floor((length(x) - frame_size) / frame_shift_size) + 1;
frames = zeros(frame_size, frame_num);
for i = 1:frame_num
    start_index = (i - 1) * frame_shift_size + 1;
    end_index = start_index + frame_size - 1;
    frames(:, i) = x(start_index:end_index);
end

% 加窗
hamming_window = hamming(frame_size);
frames = frames .* repmat(hamming_window, 1, frame_num);

% 计算功率谱密度
NFFT = 2 ^ nextpow2(frame_size);
psd = abs(fft(frames, NFFT)) .^ 2 / frame_size;

% 计算梅尔滤波器组系数
mel_filter_num = 26;
mel_filter_bank = mel_filter_bank(fs, NFFT, mel_filter_num);

% 应用梅尔滤波器组
mel_filter_output = log(mel_filter_bank * psd(1:NFFT / 2 + 1, :));

% 应用离散余弦变换
mfcc = dct(mel_filter_output);

% 计算倒谱系数
cepstral_num = 12;
cepstral_coeffs = mfcc(1:cepstral_num, :);

% 可视化倒谱系数
figure;
imagesc(cepstral_coeffs);
colorbar;
xlabel('Frame Index');
ylabel('Cepstral Coefficients');
title('MFCC Coefficients');

其中，`mel_filter_bank` 函数用于计算梅尔滤波器组系数，代码如下：

function mel_filter_bank = mel_filter_bank(fs, NFFT, mel_filter_num)
% fs：采样率
% NFFT：FFT点数
% mel_filter_num：梅尔滤波器组数量

% 计算梅尔刻度频率
mel_low_freq = 0;
mel_high_freq = hz2mel(fs / 2);
mel_freqs = linspace(mel_low_freq, mel_high_freq, mel_filter_num + 2);

% 将梅尔刻度频率转换为赫兹频率
hz_freqs = mel2hz(mel_freqs);

% 将赫兹频率转换为FFT点数下标
fft_indices = floor((NFFT + 1) * hz_freqs / fs);

% 初始化梅尔滤波器组
mel_filter_bank = zeros(mel_filter_num, NFFT / 2 + 1);

% 构建梅尔滤波器组
for i = 1:mel_filter_num
    left = fft_indices(i);
    center = fft_indices(i + 1);
    right = fft_indices(i + 2);
    for j = left:center
        mel_filter_bank(i, j) = (j - left) / (center - left);
    end
    for j = center:right
        mel_filter_bank(i, j) = (right - j) / (right - center);
    end
end

其中，`hz2mel` 和 `mel2hz` 函数用于频率单位转换，代码如下：

function mel = hz2mel(hz)
mel = 1127 * log(1 + hz / 700);

function hz = mel2hz(mel)
hz = 700 * (exp(mel / 1127) - 1);