651 lines
22 KiB
Python
Executable File
651 lines
22 KiB
Python
Executable File
"""WebRTC回声消除(AEC)演示脚本.
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该脚本用于演示WebRTC APM库的回声消除功能:
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1. 播放指定的音频文件(作为参考信号)
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2. 同时录制麦克风输入(包含回声和环境声音)
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3. 应用WebRTC回声消除处理
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4. 保存原始录音和处理后的录音，以便比较
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用法:
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python webrtc_aec_demo.py [音频文件路径]
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示例:
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python webrtc_aec_demo.py 鞠婧祎.wav
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"""
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import ctypes
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import os
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import sys
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import threading
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import time
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import wave
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from ctypes import POINTER, Structure, byref, c_bool, c_float, c_int, c_short, c_void_p
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import numpy as np
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import pyaudio
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import pygame
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import soundfile as sf
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from pygame import mixer
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# 获取DLL文件的绝对路径
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current_dir = os.path.dirname(os.path.abspath(__file__))
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project_root = os.path.dirname(current_dir)
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dll_path = os.path.join(
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project_root, "libs", "webrtc_apm", "win", "x86_64", "libwebrtc_apm.dll"
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)
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# 加载DLL
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try:
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apm_lib = ctypes.CDLL(dll_path)
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print(f"成功加载WebRTC APM库: {dll_path}")
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except Exception as e:
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print(f"加载WebRTC APM库失败: {e}")
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sys.exit(1)
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# 定义结构体和枚举类型
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class DownmixMethod(ctypes.c_int):
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AverageChannels = 0
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UseFirstChannel = 1
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class NoiseSuppressionLevel(ctypes.c_int):
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Low = 0
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Moderate = 1
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High = 2
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VeryHigh = 3
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class GainControllerMode(ctypes.c_int):
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AdaptiveAnalog = 0
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AdaptiveDigital = 1
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FixedDigital = 2
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class ClippingPredictorMode(ctypes.c_int):
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ClippingEventPrediction = 0
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AdaptiveStepClippingPeakPrediction = 1
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FixedStepClippingPeakPrediction = 2
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# 定义Pipeline结构体
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class Pipeline(Structure):
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_fields_ = [
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("MaximumInternalProcessingRate", c_int),
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("MultiChannelRender", c_bool),
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("MultiChannelCapture", c_bool),
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("CaptureDownmixMethod", c_int),
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]
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# 定义PreAmplifier结构体
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class PreAmplifier(Structure):
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_fields_ = [("Enabled", c_bool), ("FixedGainFactor", c_float)]
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# 定义AnalogMicGainEmulation结构体
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class AnalogMicGainEmulation(Structure):
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_fields_ = [("Enabled", c_bool), ("InitialLevel", c_int)]
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# 定义CaptureLevelAdjustment结构体
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class CaptureLevelAdjustment(Structure):
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_fields_ = [
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("Enabled", c_bool),
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("PreGainFactor", c_float),
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("PostGainFactor", c_float),
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("MicGainEmulation", AnalogMicGainEmulation),
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]
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# 定义HighPassFilter结构体
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class HighPassFilter(Structure):
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_fields_ = [("Enabled", c_bool), ("ApplyInFullBand", c_bool)]
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# 定义EchoCanceller结构体
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class EchoCanceller(Structure):
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_fields_ = [
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("Enabled", c_bool),
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("MobileMode", c_bool),
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("ExportLinearAecOutput", c_bool),
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("EnforceHighPassFiltering", c_bool),
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]
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# 定义NoiseSuppression结构体
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class NoiseSuppression(Structure):
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_fields_ = [
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("Enabled", c_bool),
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("NoiseLevel", c_int),
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("AnalyzeLinearAecOutputWhenAvailable", c_bool),
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]
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# 定义TransientSuppression结构体
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class TransientSuppression(Structure):
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_fields_ = [("Enabled", c_bool)]
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# 定义ClippingPredictor结构体
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class ClippingPredictor(Structure):
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_fields_ = [
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("Enabled", c_bool),
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("PredictorMode", c_int),
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("WindowLength", c_int),
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("ReferenceWindowLength", c_int),
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("ReferenceWindowDelay", c_int),
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("ClippingThreshold", c_float),
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("CrestFactorMargin", c_float),
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("UsePredictedStep", c_bool),
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]
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# 定义AnalogGainController结构体
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class AnalogGainController(Structure):
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_fields_ = [
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("Enabled", c_bool),
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("StartupMinVolume", c_int),
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("ClippedLevelMin", c_int),
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("EnableDigitalAdaptive", c_bool),
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("ClippedLevelStep", c_int),
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("ClippedRatioThreshold", c_float),
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("ClippedWaitFrames", c_int),
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("Predictor", ClippingPredictor),
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]
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# 定义GainController1结构体
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class GainController1(Structure):
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_fields_ = [
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("Enabled", c_bool),
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("ControllerMode", c_int),
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("TargetLevelDbfs", c_int),
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("CompressionGainDb", c_int),
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("EnableLimiter", c_bool),
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("AnalogController", AnalogGainController),
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]
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# 定义InputVolumeController结构体
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class InputVolumeController(Structure):
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_fields_ = [("Enabled", c_bool)]
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# 定义AdaptiveDigital结构体
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class AdaptiveDigital(Structure):
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_fields_ = [
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("Enabled", c_bool),
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("HeadroomDb", c_float),
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("MaxGainDb", c_float),
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("InitialGainDb", c_float),
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("MaxGainChangeDbPerSecond", c_float),
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("MaxOutputNoiseLevelDbfs", c_float),
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]
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# 定义FixedDigital结构体
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class FixedDigital(Structure):
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_fields_ = [("GainDb", c_float)]
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# 定义GainController2结构体
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class GainController2(Structure):
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_fields_ = [
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("Enabled", c_bool),
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("VolumeController", InputVolumeController),
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("AdaptiveController", AdaptiveDigital),
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("FixedController", FixedDigital),
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]
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# 定义完整的Config结构体
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class Config(Structure):
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_fields_ = [
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("PipelineConfig", Pipeline),
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("PreAmp", PreAmplifier),
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("LevelAdjustment", CaptureLevelAdjustment),
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("HighPass", HighPassFilter),
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("Echo", EchoCanceller),
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("NoiseSuppress", NoiseSuppression),
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("TransientSuppress", TransientSuppression),
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("GainControl1", GainController1),
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("GainControl2", GainController2),
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]
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# 定义DLL函数原型
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apm_lib.WebRTC_APM_Create.restype = c_void_p
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apm_lib.WebRTC_APM_Create.argtypes = []
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apm_lib.WebRTC_APM_Destroy.restype = None
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apm_lib.WebRTC_APM_Destroy.argtypes = [c_void_p]
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apm_lib.WebRTC_APM_CreateStreamConfig.restype = c_void_p
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apm_lib.WebRTC_APM_CreateStreamConfig.argtypes = [c_int, c_int]
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apm_lib.WebRTC_APM_DestroyStreamConfig.restype = None
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apm_lib.WebRTC_APM_DestroyStreamConfig.argtypes = [c_void_p]
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apm_lib.WebRTC_APM_ApplyConfig.restype = c_int
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apm_lib.WebRTC_APM_ApplyConfig.argtypes = [c_void_p, POINTER(Config)]
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apm_lib.WebRTC_APM_ProcessReverseStream.restype = c_int
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apm_lib.WebRTC_APM_ProcessReverseStream.argtypes = [
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c_void_p,
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POINTER(c_short),
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c_void_p,
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c_void_p,
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POINTER(c_short),
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]
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apm_lib.WebRTC_APM_ProcessStream.restype = c_int
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apm_lib.WebRTC_APM_ProcessStream.argtypes = [
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c_void_p,
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POINTER(c_short),
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c_void_p,
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c_void_p,
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POINTER(c_short),
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]
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apm_lib.WebRTC_APM_SetStreamDelayMs.restype = None
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apm_lib.WebRTC_APM_SetStreamDelayMs.argtypes = [c_void_p, c_int]
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def create_apm_config():
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"""创建WebRTC APM配置 - 优化为保留自然语音，减少错误码-11问题"""
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config = Config()
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# 设置Pipeline配置 - 使用标准采样率避免重采样问题
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config.PipelineConfig.MaximumInternalProcessingRate = 16000 # WebRTC优化频率
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config.PipelineConfig.MultiChannelRender = False
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config.PipelineConfig.MultiChannelCapture = False
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config.PipelineConfig.CaptureDownmixMethod = DownmixMethod.AverageChannels
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# 设置PreAmplifier配置 - 减少预放大干扰
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config.PreAmp.Enabled = False # 关闭预放大，避免失真
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config.PreAmp.FixedGainFactor = 1.0 # 不增益
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# 设置LevelAdjustment配置 - 简化电平调整
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config.LevelAdjustment.Enabled = False # 禁用电平调整以减少处理冲突
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config.LevelAdjustment.PreGainFactor = 1.0
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config.LevelAdjustment.PostGainFactor = 1.0
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config.LevelAdjustment.MicGainEmulation.Enabled = False
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config.LevelAdjustment.MicGainEmulation.InitialLevel = 100 # 降低初始电平避免过饱和
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# 设置HighPassFilter配置 - 使用标准高通滤波
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config.HighPass.Enabled = True # 启用高通滤波器移除低频噪声
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config.HighPass.ApplyInFullBand = True # 在全频段应用，更好的兼容性
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# 设置EchoCanceller配置 - 优化回声消除
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config.Echo.Enabled = True # 启用回声消除
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config.Echo.MobileMode = False # 使用标准模式而非移动模式以获取更好效果
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config.Echo.ExportLinearAecOutput = False
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config.Echo.EnforceHighPassFiltering = True # 启用强制高通滤波，帮助消除低频回声
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# 设置NoiseSuppression配置 - 中等强度噪声抑制
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config.NoiseSuppress.Enabled = True
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config.NoiseSuppress.NoiseLevel = NoiseSuppressionLevel.Moderate # 中等级别抑制
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config.NoiseSuppress.AnalyzeLinearAecOutputWhenAvailable = True
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# 设置TransientSuppression配置
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config.TransientSuppress.Enabled = False # 关闭瞬态抑制，避免切割语音
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# 设置GainController1配置 - 轻度增益控制
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config.GainControl1.Enabled = True # 启用增益控制
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config.GainControl1.ControllerMode = GainControllerMode.AdaptiveDigital
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config.GainControl1.TargetLevelDbfs = 3 # 降低目标电平(更积极的控制)
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config.GainControl1.CompressionGainDb = 9 # 适中的压缩增益
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config.GainControl1.EnableLimiter = True # 启用限制器
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# AnalogGainController
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config.GainControl1.AnalogController.Enabled = False # 关闭模拟增益控制
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config.GainControl1.AnalogController.StartupMinVolume = 0
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config.GainControl1.AnalogController.ClippedLevelMin = 70
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config.GainControl1.AnalogController.EnableDigitalAdaptive = False
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config.GainControl1.AnalogController.ClippedLevelStep = 15
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config.GainControl1.AnalogController.ClippedRatioThreshold = 0.1
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config.GainControl1.AnalogController.ClippedWaitFrames = 300
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# ClippingPredictor
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predictor = config.GainControl1.AnalogController.Predictor
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predictor.Enabled = False
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predictor.PredictorMode = ClippingPredictorMode.ClippingEventPrediction
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predictor.WindowLength = 5
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predictor.ReferenceWindowLength = 5
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predictor.ReferenceWindowDelay = 5
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predictor.ClippingThreshold = -1.0
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predictor.CrestFactorMargin = 3.0
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predictor.UsePredictedStep = True
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# 设置GainController2配置 - 禁用以避免冲突
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config.GainControl2.Enabled = False
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config.GainControl2.VolumeController.Enabled = False
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config.GainControl2.AdaptiveController.Enabled = False
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config.GainControl2.AdaptiveController.HeadroomDb = 5.0
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config.GainControl2.AdaptiveController.MaxGainDb = 30.0
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config.GainControl2.AdaptiveController.InitialGainDb = 15.0
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config.GainControl2.AdaptiveController.MaxGainChangeDbPerSecond = 6.0
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config.GainControl2.AdaptiveController.MaxOutputNoiseLevelDbfs = -50.0
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config.GainControl2.FixedController.GainDb = 0.0
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return config
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# 参考音频缓冲区（用于存储扬声器输出）
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reference_buffer = []
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reference_lock = threading.Lock()
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def record_playback_audio(chunk_size, sample_rate, channels):
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"""录制扬声器输出的音频（更准确的参考信号）"""
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global reference_buffer
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# 注：这是理想情况下的实现，但Windows下PyAudio通常无法直接录制扬声器输出
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# 实际应用中，需要使用其他方法捕获系统音频输出
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try:
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p = pyaudio.PyAudio()
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# 尝试创建一个从默认输出设备录制的流（部分系统支持）
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# 注意：这在大多数系统上不起作用，这里只是作为示例
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loopback_stream = p.open(
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format=pyaudio.paInt16,
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channels=channels,
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rate=sample_rate,
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input=True,
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frames_per_buffer=chunk_size,
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input_device_index=None, # 尝试使用默认输出设备作为输入源
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)
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# 开始录制
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while True:
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try:
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data = loopback_stream.read(chunk_size, exception_on_overflow=False)
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with reference_lock:
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reference_buffer.append(data)
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except OSError:
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break
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# 保持缓冲区大小合理
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with reference_lock:
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if len(reference_buffer) > 100: # 保持约2秒的缓冲
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reference_buffer = reference_buffer[-100:]
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except Exception as e:
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print(f"无法录制系统音频: {e}")
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finally:
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try:
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if "loopback_stream" in locals() and loopback_stream:
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loopback_stream.stop_stream()
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loopback_stream.close()
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if "p" in locals() and p:
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p.terminate()
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except Exception:
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pass
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def aec_demo(audio_file):
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"""WebRTC回声消除演示主函数."""
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# 检查音频文件是否存在
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if not os.path.exists(audio_file):
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print(f"错误: 找不到音频文件 {audio_file}")
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return
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# 音频参数设置 - 使用WebRTC优化的音频参数
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SAMPLE_RATE = 16000 # 采样率16kHz (WebRTC AEC优化采样率)
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CHANNELS = 1 # 单声道
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CHUNK = 160 # 每帧样本数(10ms @ 16kHz，WebRTC的标准帧大小)
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FORMAT = pyaudio.paInt16 # 16位PCM格式
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# 初始化PyAudio
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p = pyaudio.PyAudio()
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# 列出所有可用的音频设备信息供参考
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print("\n可用音频设备:")
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for i in range(p.get_device_count()):
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dev_info = p.get_device_info_by_index(i)
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print(f"设备 {i}: {dev_info['name']}")
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print(f" - 输入通道: {dev_info['maxInputChannels']}")
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print(f" - 输出通道: {dev_info['maxOutputChannels']}")
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print(f" - 默认采样率: {dev_info['defaultSampleRate']}")
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print("")
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# 打开麦克风输入流
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input_stream = p.open(
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format=FORMAT,
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channels=CHANNELS,
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rate=SAMPLE_RATE,
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input=True,
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frames_per_buffer=CHUNK,
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)
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# 初始化pygame用于播放音频
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pygame.init()
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mixer.init(frequency=SAMPLE_RATE, size=-16, channels=CHANNELS, buffer=CHUNK * 4)
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# 加载参考音频文件
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print(f"加载音频文件: {audio_file}")
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# 读取参考音频文件并转换采样率/通道数
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# 注意：这里使用soundfile库加载音频文件以支持多种格式并进行重采样
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try:
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print("加载参考音频...")
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# 使用soundfile库读取原始音频
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ref_audio_data, orig_sr = sf.read(audio_file, dtype="int16")
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print(
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f"原始音频: 采样率={orig_sr}, 通道数="
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f"{ref_audio_data.shape[1] if len(ref_audio_data.shape) > 1 else 1}"
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)
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# 转换为单声道(如果是立体声)
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if len(ref_audio_data.shape) > 1 and ref_audio_data.shape[1] > 1:
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ref_audio_data = ref_audio_data.mean(axis=1).astype(np.int16)
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# 转换采样率(如果需要)
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if orig_sr != SAMPLE_RATE:
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print(f"重采样参考音频从{orig_sr}Hz到{SAMPLE_RATE}Hz...")
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# 使用librosa或scipy进行重采样
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from scipy import signal
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ref_audio_data = signal.resample(
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ref_audio_data, int(len(ref_audio_data) * SAMPLE_RATE / orig_sr)
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).astype(np.int16)
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# 保存为临时wav文件供pygame播放
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temp_wav_path = os.path.join(current_dir, "temp_reference.wav")
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with wave.open(temp_wav_path, "wb") as wf:
|
||
wf.setnchannels(1)
|
||
wf.setsampwidth(2) # 2字节(16位)
|
||
wf.setframerate(SAMPLE_RATE)
|
||
wf.writeframes(ref_audio_data.tobytes())
|
||
|
||
# 将参考音频分成CHUNK大小的帧
|
||
ref_audio_frames = []
|
||
for i in range(0, len(ref_audio_data), CHUNK):
|
||
if i + CHUNK <= len(ref_audio_data):
|
||
ref_audio_frames.append(ref_audio_data[i : i + CHUNK])
|
||
else:
|
||
# 最后一帧不足CHUNK大小，补零
|
||
last_frame = np.zeros(CHUNK, dtype=np.int16)
|
||
last_frame[: len(ref_audio_data) - i] = ref_audio_data[i:]
|
||
ref_audio_frames.append(last_frame)
|
||
|
||
print(f"参考音频准备完成，共{len(ref_audio_frames)}帧")
|
||
|
||
# 加载处理后的临时WAV文件
|
||
mixer.music.load(temp_wav_path)
|
||
except Exception as e:
|
||
print(f"加载参考音频时出错: {e}")
|
||
sys.exit(1)
|
||
|
||
# 创建WebRTC APM实例
|
||
apm = apm_lib.WebRTC_APM_Create()
|
||
|
||
# 应用APM配置
|
||
config = create_apm_config()
|
||
result = apm_lib.WebRTC_APM_ApplyConfig(apm, byref(config))
|
||
if result != 0:
|
||
print(f"警告: APM配置应用失败，错误码: {result}")
|
||
|
||
# 创建流配置
|
||
stream_config = apm_lib.WebRTC_APM_CreateStreamConfig(SAMPLE_RATE, CHANNELS)
|
||
|
||
# 设置较小的延迟时间以更准确匹配参考信号和麦克风信号
|
||
apm_lib.WebRTC_APM_SetStreamDelayMs(apm, 50)
|
||
|
||
# 创建录音缓冲区
|
||
original_frames = []
|
||
processed_frames = []
|
||
reference_frames = []
|
||
|
||
# 等待一会让音频系统准备好
|
||
time.sleep(0.5)
|
||
|
||
print("开始录制和处理...")
|
||
print("播放参考音频...")
|
||
|
||
mixer.music.play()
|
||
|
||
# 录制持续时间(根据音频文件长度)
|
||
try:
|
||
sound_length = mixer.Sound(temp_wav_path).get_length()
|
||
recording_time = sound_length if sound_length > 0 else 10
|
||
except Exception:
|
||
recording_time = 10 # 如果无法获取长度，默认10秒
|
||
|
||
recording_time += 1 # 额外1秒确保捕获所有音频
|
||
|
||
start_time = time.time()
|
||
current_ref_frame_index = 0
|
||
try:
|
||
while time.time() - start_time < recording_time:
|
||
# 从麦克风读取一帧数据
|
||
input_data = input_stream.read(CHUNK, exception_on_overflow=False)
|
||
|
||
# 保存原始录音
|
||
original_frames.append(input_data)
|
||
|
||
# 将输入数据转换为short数组
|
||
input_array = np.frombuffer(input_data, dtype=np.int16)
|
||
input_ptr = input_array.ctypes.data_as(POINTER(c_short))
|
||
|
||
# 获取当前参考音频帧
|
||
if current_ref_frame_index < len(ref_audio_frames):
|
||
ref_array = ref_audio_frames[current_ref_frame_index]
|
||
reference_frames.append(ref_array.tobytes())
|
||
current_ref_frame_index += 1
|
||
else:
|
||
# 如果参考音频播放完毕，使用静音帧
|
||
ref_array = np.zeros(CHUNK, dtype=np.int16)
|
||
reference_frames.append(ref_array.tobytes())
|
||
|
||
ref_ptr = ref_array.ctypes.data_as(POINTER(c_short))
|
||
|
||
# 创建输出缓冲区
|
||
output_array = np.zeros(CHUNK, dtype=np.int16)
|
||
output_ptr = output_array.ctypes.data_as(POINTER(c_short))
|
||
|
||
# 重要：先处理参考信号（扬声器输出）
|
||
# 创建参考信号的输出缓冲区（虽然不使用但必须提供）
|
||
ref_output_array = np.zeros(CHUNK, dtype=np.int16)
|
||
ref_output_ptr = ref_output_array.ctypes.data_as(POINTER(c_short))
|
||
|
||
result_reverse = apm_lib.WebRTC_APM_ProcessReverseStream(
|
||
apm, ref_ptr, stream_config, stream_config, ref_output_ptr
|
||
)
|
||
|
||
if result_reverse != 0:
|
||
print(f"\r警告: 参考信号处理失败，错误码: {result_reverse}")
|
||
|
||
# 然后处理麦克风信号，应用回声消除
|
||
result = apm_lib.WebRTC_APM_ProcessStream(
|
||
apm, input_ptr, stream_config, stream_config, output_ptr
|
||
)
|
||
|
||
if result != 0:
|
||
print(f"\r警告: 处理失败，错误码: {result}")
|
||
|
||
# 保存处理后的音频帧
|
||
processed_frames.append(output_array.tobytes())
|
||
|
||
# 计算并显示进度
|
||
progress = (time.time() - start_time) / recording_time * 100
|
||
sys.stdout.write(f"\r处理进度: {progress:.1f}%")
|
||
sys.stdout.flush()
|
||
|
||
except KeyboardInterrupt:
|
||
print("\n录制被用户中断")
|
||
finally:
|
||
print("\n录制和处理完成")
|
||
|
||
# 停止播放
|
||
mixer.music.stop()
|
||
|
||
# 关闭音频流
|
||
input_stream.stop_stream()
|
||
input_stream.close()
|
||
|
||
# 释放APM资源
|
||
apm_lib.WebRTC_APM_DestroyStreamConfig(stream_config)
|
||
apm_lib.WebRTC_APM_Destroy(apm)
|
||
|
||
# 关闭PyAudio
|
||
p.terminate()
|
||
|
||
# 保存原始录音
|
||
original_output_path = os.path.join(current_dir, "original_recording.wav")
|
||
save_wav(original_output_path, original_frames, SAMPLE_RATE, CHANNELS)
|
||
|
||
# 保存处理后的录音
|
||
processed_output_path = os.path.join(current_dir, "processed_recording.wav")
|
||
save_wav(processed_output_path, processed_frames, SAMPLE_RATE, CHANNELS)
|
||
|
||
# 保存参考音频（播放的音频）
|
||
reference_output_path = os.path.join(current_dir, "reference_playback.wav")
|
||
save_wav(reference_output_path, reference_frames, SAMPLE_RATE, CHANNELS)
|
||
|
||
# 删除临时文件
|
||
if os.path.exists(temp_wav_path):
|
||
try:
|
||
os.remove(temp_wav_path)
|
||
except Exception:
|
||
pass
|
||
|
||
print(f"原始录音已保存至: {original_output_path}")
|
||
print(f"处理后的录音已保存至: {processed_output_path}")
|
||
print(f"参考音频已保存至: {reference_output_path}")
|
||
|
||
# 退出pygame
|
||
pygame.quit()
|
||
|
||
|
||
def save_wav(file_path, frames, sample_rate, channels):
|
||
"""将音频帧保存为WAV文件."""
|
||
with wave.open(file_path, "wb") as wf:
|
||
wf.setnchannels(channels)
|
||
wf.setsampwidth(2) # 2字节(16位)
|
||
wf.setframerate(sample_rate)
|
||
if isinstance(frames[0], bytes):
|
||
wf.writeframes(b"".join(frames))
|
||
else:
|
||
wf.writeframes(b"".join([f for f in frames if isinstance(f, bytes)]))
|
||
|
||
|
||
if __name__ == "__main__":
|
||
# 获取命令行参数
|
||
if len(sys.argv) > 1:
|
||
audio_file = sys.argv[1]
|
||
else:
|
||
# 默认使用scripts目录下的鞠婧祎.wav
|
||
audio_file = os.path.join(current_dir, "鞠婧祎.wav")
|
||
|
||
# 如果默认文件不存在，尝试MP3版本
|
||
if not os.path.exists(audio_file):
|
||
audio_file = os.path.join(current_dir, "鞠婧祎.mp3")
|
||
if not os.path.exists(audio_file):
|
||
print("错误: 找不到默认音频文件，请指定要播放的音频文件路径")
|
||
print("用法: python webrtc_aec_demo.py [音频文件路径]")
|
||
sys.exit(1)
|
||
|
||
# 运行演示
|
||
aec_demo(audio_file)
|