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 维基百科 ,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

#include

#include

//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; //

format.format = DR_WAVE_FORMAT_PCM; //

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

#include

#include

//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。

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gaozhihan@vip.qq.com