音頻自動增益 與 靜音檢測 算法 附完整C代碼
阿新 • • 發佈：2018-04-22
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前面分享過一個算法《音頻增益響度分析 ReplayGain 附完整C代碼示例》
主要用於評估一定長度音頻的音量強度，
而分析之後，很多類似的需求，肯定是做音頻增益，提高音量諸如此類做法。
不過在項目實測的時候，其實真的很難定標準，
到底在什麽樣的環境下，要增大音量，還是降低。
在通訊行業一般的做法就是采用靜音檢測，
一旦檢測為靜音或者噪音，則不做處理，反之通過一定的策略進行處理。
這裏就涉及到兩個算法，一個是靜音檢測，一個是音頻增益。
增益其實沒什麽好說的，類似於數據歸一化拉伸的做法。
靜音檢測 在WebRTC中 是采用計算GMM (Gaussian Mixture Model,高斯混合模型)進行特征提取的。
在很長一段時間裏面，音頻特征 有3個主要的方法，
GMM ,Spectrogram (聲譜圖), MFCC 即 Mel-Frequency Cepstrum(Mel頻率倒譜)
恕我直言,GMM 提取的特征，其魯棒性 不如後兩者。
也不多做介紹，感興趣的同學，翻翻 維基百科 ,補補課。
當然在實際使用算法時，會由此延伸出來一些小技巧。
例如，用靜音檢測 來做音頻裁剪，或者搭配音頻增益做一些音頻增強之類的操作。
自動增益在WebRTC 源代碼文件是:analog_agc.c 和 digital_agc.c
靜音檢測 源代碼文件是: webrtc_vad.c
這個命名，有一定的歷史原因了。
經過梳理後，
增益算法為 agc.c agc.h
靜音檢測為 vad.c vad.h
增益算法的完整示例代碼：
#include <stdio.h> #include <stdlib.h> #include <stdint.h> //采用https://github.com/mackron/dr_libs/blob/master/dr_wav.h 解碼 #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 //寫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); } } } //讀取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("讀取wav文件失敗."); } //僅僅處理單通道音頻 if (channels != 1) { drwav_free(buffer); buffer = nullptr; *sampleRate = 0; *totalSampleCount = 0; } return buffer; } //分割路徑函數 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; //是否有溢出發生，增益放大以後的最大值超過了65536 int16_t echo = 0; //增益放大是否考慮回聲影響 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) { //音頻采樣率 uint32_t sampleRate = 0; //總音頻采樣數 uint64_t inSampleCount = 0; int16_t *inBuffer = wavRead_int16(in_file, &sampleRate, &inSampleCount); //如果加載成功 if (inBuffer != nullptr) { // kAgcModeAdaptiveAnalog 模擬音量調節 // kAgcModeAdaptiveDigital 自適應增益 // 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("音頻自動增益\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("按任意鍵退出程序 \n"); getchar(); return 0; }
靜音檢測完整示例代碼：
#include <stdio.h> #include <stdlib.h> #include <stdint.h> //采用https://github.com/mackron/dr_libs/blob/master/dr_wav.h 解碼 #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 //讀取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("讀取wav文件失敗."); } //僅僅處理單通道音頻 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) { //音頻采樣率 uint32_t sampleRate = 0; //總音頻采樣數 uint64_t inSampleCount = 0; int16_t *inBuffer = wavRead_int16(in_file, &sampleRate, &inSampleCount); //如果加載成功 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("靜音檢測\n"); if (argc < 2) return -1; char *in_file = argv[1]; vad(in_file); printf("按任意鍵退出程序 \n"); getchar(); return 0; }
自動增益項目地址:https://github.com/cpuimage/WebRTC_AGC
具體流程為：
加載wav(拖放wav文件到可執行文件上)->增益處理->保存為_out.wav文件
靜音檢測項目地址：https://github.com/cpuimage/WebRTC_VAD
具體流程為：
加載wav(拖放wav文件到可執行文件上)->輸出靜音檢測結果
備註 :1 為非靜音，0 為靜音
該註意的地方和參數，見代碼註釋。
用cmake即可進行編譯示例代碼，詳情見CMakeLists.txt。
若有其他相關問題或者需求也可以郵件聯系俺探討。
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音頻自動增益 與 靜音檢測 算法 附完整C代碼