当前位置：首页 > news >正文

C++中使用Essentia实现STFT/ISTFT

news 2025/7/26 14:23:01

最近在做一个项目，需要将音频送入 AI 模型进行处理。整个流程包括：

从 .wav 文件中加载音频；
进行 短时傅里叶变换（STFT）；
将变换结果输入模型；
使用 逆STFT（ISTFT） 重建回时域信号。

作为一个长期从事图像方向的 CVer，我对音频领域相对陌生。在调研后发现，和计算机视觉相比，优质的音频处理库屈指可数。而手撸 STFT / ISTFT 又繁琐、容易出错。

最终，我选择了开源音频分析库 Essentia，其功能强大、API 结构清晰，非常适合科研和快速原型验证。本文将分享如何在 C++ 中基于 Essentia 实现 STFT / ISTFT，并完成音频的重建。

🔍 什么是 Essentia？

Essentia 是由巴塞罗那庞培法布拉大学音乐技术小组（MTG）开发的开源 C++ 音频分析库，发布于 AGPLv3 许可下。

Essentia 提供了一套丰富的算法模块，覆盖以下能力：

音频 I/O 和预处理；
数字信号处理（DSP）基础块；
声学和音乐特征提取（如光谱、音调、节奏、情绪等）；
Python 包装与 Vamp 插件支持，便于快速原型与可视化。

虽然资料较少、使用门槛稍高，但其结构良好，非常适合做科研实验或工业应用中的音频前处理部分。

🛠 编译 Essentia（推荐 Docker 环境）

手动编译步骤如下：

git clone https://github.com/MTG/essentia.git
cd essentia
packaging/build_3rdparty_static_debian.sh

⚠️ 如果第三方依赖下载失败，可以手动修改 packaging/debian_3rdparty/ 下的对应脚本，将源码下载到指定目录。

接着执行：

./waf configure --with-static-examples
./waf

如果你希望跳过编译，可以从我上传的打包资源中下载使用。

📦 在 C++ 中使用 STFT

AlgorithmFactory& factory = standard::AlgorithmFactory::instance();// 1. 加载音频
Algorithm* loader = factory.create("MonoLoader", "filename", "test.wav", "sampleRate", 16000);
vector<Real> audio;
loader->output("audio").set(audio);
loader->compute();
delete loader;

设置参数：

const int frameSize = 320; 
const int hopSize = 80;    // 25% overlap

STFT 流程：

Algorithm* frameCutter = factory.create("FrameCutter","frameSize", frameSize,"hopSize", hopSize);
Algorithm* windowing = factory.create("Windowing","type", "hann","normalized", false);
Algorithm* fft = factory.create("FFT", "size", frameSize);frameCutter->input("signal").set(audio);
vector<Real> frame, windowedFrame;
vector<complex<Real>> fftFrame;frameCutter->output("frame").set(frame);
windowing->input("frame").set(frame);
windowing->output("frame").set(windowedFrame);
fft->input("frame").set(windowedFrame);
fft->output("fft").set(fftFrame);vector<vector<complex<Real>>> stftResult;while (true) {frameCutter->compute();if (frame.empty()) break;windowing->compute();fft->compute();stftResult.push_back(fftFrame);
}

🔁 实现 ISTFT

由于 Essentia 并未提供完整的 Overlap-Add 封装，我们需要仿照 librosa 逻辑手动实现。

Algorithm* ifft = factory.create("IFFT", "size", frameSize);vector<Real> window = computeLibrosaHann(frameSize);
Real windowSum = 0.0;
for (int i = 0; i < hopSize; ++i) {windowSum += window[i] * window[i];
}
const Real compensation = 1.0 / windowSum;vector<Real> reconstructedAudio(originalLength, 0.0);
vector<Real> ifftOutputFrame(frameSize);for (int i = 0; i < stftResult.size(); ++i) {ifft->input("fft").set(stftResult[i]);ifft->output("frame").set(ifftOutputFrame);ifft->compute();int pos = i * hopSize;for (int n = 0; n < frameSize && pos + n < reconstructedAudio.size(); ++n) {reconstructedAudio[pos + n] += ifftOutputFrame[n] * window[n] * compensation;}
}

🧹 后处理与音频保存

removeDCOffset(reconstructedAudio);
conservativeNormalize(reconstructedAudio, 0.99);// 保存音频
Algorithm* writer = factory.create("MonoWriter","filename", "./reconstructed.wav","sampleRate", 16000);
writer->input("audio").set(reconstructedAudio);
writer->compute();
delete writer;

🧪 代码完整示例

#include <iostream>
#include <essentia/essentia.h>
#include <essentia/algorithmfactory.h>
#include <essentia/pool.h>
#include <Eigen/Dense>
#include <unsupported/Eigen/CXX11/Tensor>
#include <numeric>
#include <cmath>using namespace std;
using namespace essentia;
using namespace essentia::standard;// Librosa风格的汉宁窗计算
vector<Real> computeLibrosaHann(int size) {vector<Real> window(size);for (int i = 0; i < size; ++i) {window[i] = sin(M_PI * i / (size - 1)) * sin(M_PI * i / (size - 1));}return window;
}// 移除直流偏移
void removeDCOffset(vector<Real>& audio) {Real dcOffset = accumulate(audio.begin(), audio.end(), 0.0) / audio.size();for (auto& sample : audio) {sample -= dcOffset;}
}// 保守归一化
void conservativeNormalize(vector<Real>& audio, Real targetPeak = 0.99) {Real peak = *max_element(audio.begin(), audio.end(),[](Real a, Real b) { return abs(a) < abs(b); });if (abs(peak) > 1e-6) {  // 避免除以0for (auto& sample : audio) {sample *= (targetPeak / abs(peak));}}
}int main() {// 初始化Essentiaessentia::init();AlgorithmFactory& factory = standard::AlgorithmFactory::instance();// 1. 加载音频Algorithm* loader = factory.create("MonoLoader","filename", "/work/000002.wav","sampleRate", 16000);vector<Real> audio;loader->output("audio").set(audio);loader->compute();delete loader;cout << "Loaded audio with " << audio.size() << " samples" << endl;// 2. STFT参数设置const int frameSize = 320;      // 与librosa默认值一致const int hopSize = 80;        // 25%重叠const int originalLength = audio.size();const string windowType = "hann";// 3. STFT处理Algorithm* frameCutter = factory.create("FrameCutter","frameSize", frameSize,"hopSize", hopSize);Algorithm* windowing = factory.create("Windowing","type", windowType,"normalized", false,"zeroPhase", false);Algorithm* fft = factory.create("FFT", "size", frameSize);frameCutter->input("signal").set(audio);vector<Real> frame, windowedFrame;frameCutter->output("frame").set(frame);windowing->input("frame").set(frame);windowing->output("frame").set(windowedFrame);vector<complex<Real>> fftFrame;fft->input("frame").set(windowedFrame);fft->output("fft").set(fftFrame);vector<vector<complex<Real>>> stftResult;// STFT处理循环while (true) {frameCutter->compute();if (frame.empty()) break;windowing->compute();fft->compute();stftResult.push_back(fftFrame);}delete frameCutter;delete windowing;delete fft;cout << "STFT completed. Frames: " << stftResult.size() << ", Bins: " << (stftResult.empty() ? 0 : stftResult[0].size()) << endl;// 4. ISTFT处理（librosa风格）Algorithm* ifft = factory.create("IFFT", "size", frameSize);// 计算窗函数和补偿因子vector<Real> window = computeLibrosaHann(frameSize);Real windowSum = 0.0;for (int i = 0; i < hopSize; ++i) {windowSum += window[i] * window[i];}const Real compensation = 1.0 / windowSum;// 重建音频初始化vector<Real> reconstructedAudio(originalLength, 0.0);vector<Real> ifftOutputFrame(frameSize);// 处理每一帧for (int i = 0; i < stftResult.size(); ++i) {// IFFT变换ifft->input("fft").set(stftResult[i]);ifft->output("frame").set(ifftOutputFrame);ifft->compute();// 重叠相加（librosa风格）int pos = i * hopSize;for (int n = 0; n < frameSize && pos + n < reconstructedAudio.size(); ++n) {reconstructedAudio[pos + n] += ifftOutputFrame[n] * window[n] * compensation;}}delete ifft;// 5. 后处理removeDCOffset(reconstructedAudio);conservativeNormalize(reconstructedAudio, 0.99);// 6. 结果验证// 计算RMS能量比auto computeRMS = [](const vector<Real>& x) {return sqrt(accumulate(x.begin(), x.end(), 0.0, [](Real sum, Real val) { return sum + val*val; }) / x.size());};Real originalRMS = computeRMS(audio);Real reconstructedRMS = computeRMS(reconstructedAudio);cout << "Volume ratio (reconstructed/original): " << reconstructedRMS / originalRMS << endl;// 7. 保存结果Algorithm* writer = factory.create("MonoWriter","filename", "./reconstructed.wav","sampleRate", 16000);writer->input("audio").set(reconstructedAudio);writer->compute();delete writer;essentia::shutdown();return 0;
}

🧩 CMake 配置示例

Essentia 依赖众多第三方库，下面是一个完整的 CMakeLists.txt 配置参考：

cmake_minimum_required(VERSION 3.10)
project(gcrn_cpp)set(CMAKE_CXX_STANDARD 17)file(GLOB_RECURSE CORE_SOURCE_FILES ${CMAKE_CURRENT_LIST_DIR}/source/*.cpp)
include_directories(${CMAKE_CURRENT_LIST_DIR}/3rdparty)
link_directories(${CMAKE_CURRENT_LIST_DIR}/libs/)# 设置 PKG_CONFIG 路径
set(ENV{PKG_CONFIG_PATH} "/essentia-master/packaging/debian_3rdparty/lib/pkgconfig:$ENV{PKG_CONFIG_PATH}")
find_package(PkgConfig REQUIRED)# 依赖库查找
pkg_check_modules(SWRESAMPLE REQUIRED libswresample)
pkg_check_modules(AVCODEC REQUIRED libavcodec)
pkg_check_modules(AVFORMAT REQUIRED libavformat)
pkg_check_modules(SAMPLERATE REQUIRED samplerate)
pkg_check_modules(FFTW3 REQUIRED fftw3f)
pkg_check_modules(CHROMAPRINT REQUIRED libchromaprint)
pkg_check_modules(TAGLIB REQUIRED taglib)
pkg_check_modules(YAML REQUIRED yaml-0.1)
pkg_check_modules(EIGEN3 REQUIRED eigen3)include_directories(${EIGEN3_INCLUDE_DIRS})
link_directories(${SAMPLERATE_LIBRARY_DIRS})add_executable(gcrn_cpp main.cpp ${CORE_SOURCE_FILES})
target_link_libraries(gcrn_cpp PRIVATEessentia${CHROMAPRINT_LIBRARIES}${SWRESAMPLE_LIBRARIES}${SAMPLERATE_LIBRARIES}${AVFORMAT_LIBRARIES}${AVCODEC_LIBRARIES}${AVUTIL_LIBRARIES}${FFTW3_LIBRARIES}${TAGLIB_LIBRARIES}${YAML_LIBRARIES}pthread dl m z
)