转自：https://www.cnblogs.com/cpuimage/p/8908551.html
前面分享过一个算法《音频增益响度分析 ReplayGain 附完整C代码示例》
主要用于评估一定长度音频的音量强度，
而分析之后，很多类似的需求，肯定是做音频增益，提高音量诸如此类做法。
不过在项目实测的时候，其实真的很难定标准，
到底在什么样的环境下，要增大音量，还是降低。
在通讯行业一般的做法就是采用静音检测，
一旦检测为静音或者噪音，则不做处理，反之通过一定的策略进行处理。
这里就涉及到两个算法，一个是静音检测，一个是音频增益。
增益其实没什么好说的，类似于数据归一化拉伸的做法。
静音检测 在WebRTC中 是采用计算GMM (Gaussian Mixture Model,高斯混合模型)进行特征提取的。
在很长一段时间里面，音频特征 有3个主要的方法，
GMM ,Spectrogram (声谱图), MFCC 即 Mel-Frequency Cepstrum(Mel频率倒谱)
恕我直言,GMM 提取的特征，其鲁棒性 不如后两者。
也不多做介绍，感兴趣的同学，翻翻 * ,补补课。
当然在实际使用算法时，会由此延伸出来一些小技巧。
例如，用静音检测 来做音频裁剪，或者搭配音频增益做一些音频增强之类的操作。
自动增益在WebRTC 源代码文件是:analog_agc.c 和 digital_agc.c
静音检测 源代码文件是: webrtc_vad.c
这个命名，有一定的历史原因了。
经过梳理后，
增益算法为 agc.c agc.h
静音检测为 vad.c vad.h
增益算法的完整示例代码：
#include <stdio.h>
#include <stdlib.h>
#include <stdint.h>
//采用https://github.com/mackron/dr_libs/blob/master/dr_wav.h 解码
#define DR_WAV_IMPLEMENTATION
#include "dr_wav.h"
#include "agc.h" #ifndef nullptr
#define nullptr 0
#endif #ifndef MIN
#define MIN(A, B) ((A) < (B) ? (A) : (B))
#endif //写wav文件
void wavWrite_int16(char *filename, int16_t *buffer, size_t sampleRate, size_t totalSampleCount) {
drwav_data_format format = {};
format.container = drwav_container_riff; // <-- drwav_container_riff = normal WAV files, drwav_container_w64 = Sony Wave64.
format.format = DR_WAVE_FORMAT_PCM; // <-- Any of the DR_WAVE_FORMAT_* codes.
format.channels = 1;
format.sampleRate = (drwav_uint32) sampleRate;
format.bitsPerSample = 16;
drwav *pWav = drwav_open_file_write(filename, &format);
if (pWav) {
drwav_uint64 samplesWritten = drwav_write(pWav, totalSampleCount, buffer);
drwav_uninit(pWav);
if (samplesWritten != totalSampleCount) {
fprintf(stderr, "ERROR\n");
exit(1);
}
}
} //读取wav文件
int16_t *wavRead_int16(char *filename, uint32_t *sampleRate, uint64_t *totalSampleCount) {
unsigned int channels;
int16_t *buffer = drwav_open_and_read_file_s16(filename, &channels, sampleRate, totalSampleCount);
if (buffer == nullptr) {
printf("读取wav文件失败.");
}
//仅仅处理单通道音频
if (channels != 1) {
drwav_free(buffer);
buffer = nullptr;
*sampleRate = 0;
*totalSampleCount = 0;
}
return buffer;
} //分割路径函数
void splitpath(const char *path, char *drv, char *dir, char *name, char *ext) {
const char *end;
const char *p;
const char *s;
if (path[0] && path[1] == ':') {
if (drv) {
*drv++ = *path++;
*drv++ = *path++;
*drv = '\0';
}
} else if (drv)
*drv = '\0';
for (end = path; *end && *end != ':';)
end++;
for (p = end; p > path && *--p != '\\' && *p != '/';)
if (*p == '.') {
end = p;
break;
}
if (ext)
for (s = end; (*ext = *s++);)
ext++;
for (p = end; p > path;)
if (*--p == '\\' || *p == '/') {
p++;
break;
}
if (name) {
for (s = p; s < end;)
*name++ = *s++;
*name = '\0';
}
if (dir) {
for (s = path; s < p;)
*dir++ = *s++;
*dir = '\0';
}
} int agcProcess(int16_t *buffer, uint32_t sampleRate, size_t samplesCount, int16_t agcMode) {
if (buffer == nullptr) return -1;
if (samplesCount == 0) return -1;
WebRtcAgcConfig agcConfig;
agcConfig.compressionGaindB = 9; // default 9 dB
agcConfig.limiterEnable = 1; // default kAgcTrue (on)
agcConfig.targetLevelDbfs = 3; // default 3 (-3 dBOv)
int minLevel = 0;
int maxLevel = 255;
size_t samples = MIN(160, sampleRate / 100);
if (samples == 0) return -1;
const int maxSamples = 320;
int16_t *input = buffer;
size_t nTotal = (samplesCount / samples);
void *agcInst = WebRtcAgc_Create();
if (agcInst == NULL) return -1;
int status = WebRtcAgc_Init(agcInst, minLevel, maxLevel, agcMode, sampleRate);
if (status != 0) {
printf("WebRtcAgc_Init fail\n");
WebRtcAgc_Free(agcInst);
return -1;
}
status = WebRtcAgc_set_config(agcInst, agcConfig);
if (status != 0) {
printf("WebRtcAgc_set_config fail\n");
WebRtcAgc_Free(agcInst);
return -1;
}
size_t num_bands = 1;
int inMicLevel, outMicLevel = -1;
int16_t out_buffer[maxSamples];
int16_t *out16 = out_buffer;
uint8_t saturationWarning = 1; //是否有溢出发生，增益放大以后的最大值超过了65536
int16_t echo = 0; //增益放大是否考虑回声影响
for (int i = 0; i < nTotal; i++) {
inMicLevel = 0;
int nAgcRet = WebRtcAgc_Process(agcInst, (const int16_t *const *) &input, num_bands, samples,
(int16_t *const *) &out16, inMicLevel, &outMicLevel, echo,
&saturationWarning); if (nAgcRet != 0) {
printf("failed in WebRtcAgc_Process\n");
WebRtcAgc_Free(agcInst);
return -1;
}
memcpy(input, out_buffer, samples * sizeof(int16_t));
input += samples;
}
WebRtcAgc_Free(agcInst);
return 1;
} void auto_gain(char *in_file, char *out_file) {
//音频采样率
uint32_t sampleRate = 0;
//总音频采样数
uint64_t inSampleCount = 0;
int16_t *inBuffer = wavRead_int16(in_file, &sampleRate, &inSampleCount);
//如果加载成功
if (inBuffer != nullptr) {
// kAgcModeAdaptiveAnalog 模拟音量调节
// kAgcModeAdaptiveDigital 自适应增益
// kAgcModeFixedDigital 固定增益
agcProcess(inBuffer, sampleRate, inSampleCount, kAgcModeAdaptiveDigital);
wavWrite_int16(out_file, inBuffer, sampleRate, inSampleCount);
free(inBuffer);
}
} int main(int argc, char *argv[]) {
printf("WebRTC Automatic Gain Control\n");
printf("博客:http://cpuimage.cnblogs.com/\n");
printf("音频自动增益\n");
if (argc < 2)
return -1;
char *in_file = argv[1];
char drive[3];
char dir[256];
char fname[256];
char ext[256];
char out_file[1024];
splitpath(in_file, drive, dir, fname, ext);
sprintf(out_file, "%s%s%s_out%s", drive, dir, fname, ext);
auto_gain(in_file, out_file); printf("按任意键退出程序 \n");
getchar();
return 0;
}
静音检测完整示例代码：
#include <stdio.h>
#include <stdlib.h>
#include <stdint.h>
//采用https://github.com/mackron/dr_libs/blob/master/dr_wav.h 解码
#define DR_WAV_IMPLEMENTATION #include "dr_wav.h"
#include "vad.h" #ifndef nullptr
#define nullptr 0
#endif #ifndef MIN
#define MIN(A, B) ((A) < (B) ? (A) : (B))
#endif #ifndef MAX
#define MAX(A, B) ((A) > (B) ? (A) : (B))
#endif //读取wav文件
int16_t *wavRead_int16(char *filename, uint32_t *sampleRate, uint64_t *totalSampleCount) {
unsigned int channels;
int16_t *buffer = drwav_open_and_read_file_s16(filename, &channels, sampleRate, totalSampleCount);
if (buffer == nullptr) {
printf("读取wav文件失败.");
}
//仅仅处理单通道音频
if (channels != 1) {
drwav_free(buffer);
buffer = nullptr;
*sampleRate = 0;
*totalSampleCount = 0;
}
return buffer;
} int vadProcess(int16_t *buffer, uint32_t sampleRate, size_t samplesCount, int16_t vad_mode, int per_ms_frames) {
if (buffer == nullptr) return -1;
if (samplesCount == 0) return -1;
// kValidRates : 8000, 16000, 32000, 48000
// 10, 20 or 30 ms frames
per_ms_frames = MAX(MIN(30, per_ms_frames), 10);
size_t samples = sampleRate * per_ms_frames / 1000;
if (samples == 0) return -1;
int16_t *input = buffer;
size_t nTotal = (samplesCount / samples); void *vadInst = WebRtcVad_Create();
if (vadInst == NULL) return -1;
int status = WebRtcVad_Init(vadInst);
if (status != 0) {
printf("WebRtcVad_Init fail\n");
WebRtcVad_Free(vadInst);
return -1;
}
status = WebRtcVad_set_mode(vadInst, vad_mode);
if (status != 0) {
printf("WebRtcVad_set_mode fail\n");
WebRtcVad_Free(vadInst);
return -1;
}
printf("Activity ： \n");
for (int i = 0; i < nTotal; i++) {
int nVadRet = WebRtcVad_Process(vadInst, sampleRate, input, samples);
if (nVadRet == -1) {
printf("failed in WebRtcVad_Process\n");
WebRtcVad_Free(vadInst);
return -1;
} else {
// output result
printf(" %d \t", nVadRet);
}
input += samples;
}
printf("\n");
WebRtcVad_Free(vadInst);
return 1;
} void vad(char *in_file) {
//音频采样率
uint32_t sampleRate = 0;
//总音频采样数
uint64_t inSampleCount = 0;
int16_t *inBuffer = wavRead_int16(in_file, &sampleRate, &inSampleCount);
//如果加载成功
if (inBuffer != nullptr) {
// Aggressiveness mode (0, 1, 2, or 3)
int16_t mode = 1;
int per_ms = 30;
vadProcess(inBuffer, sampleRate, inSampleCount, mode, per_ms);
free(inBuffer);
}
} int main(int argc, char *argv[]) {
printf("WebRTC Voice Activity Detector\n");
printf("博客:http://cpuimage.cnblogs.com/\n");
printf("静音检测\n");
if (argc < 2)
return -1;
char *in_file = argv[1];
vad(in_file);
printf("按任意键退出程序 \n");
getchar();
return 0;
}
自动增益项目地址:https://github.com/cpuimage/WebRTC_AGC
具体流程为：
加载wav(拖放wav文件到可执行文件上)->增益处理->保存为_out.wav文件
静音检测项目地址：https://github.com/cpuimage/WebRTC_VAD
具体流程为：
加载wav(拖放wav文件到可执行文件上)->输出静音检测结果
备注 :1 为非静音，0 为静音
该注意的地方和参数，见代码注释。
用cmake即可进行编译示例代码，详情见CMakeLists.txt。
若有其他相关问题或者需求也可以邮件联系俺探讨。
邮箱地址是:
gaozhihan@vip.qq.com