#-*- coding: utf-8 -*- import os import wave from time import sleep import numpy as np SUCCESS = 0 FAIL = 1 # 需要添加录音互斥功能能,某些功能开启的时候录音暂时关闭 def ZCR(curFrame): # 过零率 tmp1 = curFrame[:-1] tmp2 = curFrame[1:] sings = (tmp1 * tmp2 <= 0) diffs = (tmp1 - tmp2) > 0.02 zcr = np.sum(sings * diffs) return zcr def STE(curFrame): # 短时能量 amp = np.sum(np.abs(curFrame)) return amp class Vad(object): def __init__(self): # 初始短时能量高门限 self.amp1 = 140 # 初始短时能量低门限 self.amp2 = 120 # 初始短时过零率高门限 self.zcr1 = 10 # 初始短时过零率低门限 self.zcr2 = 5 # 允许最大静音长度 self.maxsilence = 100 # 语音的最短长度 self.minlen = 40 # 偏移值 self.offsets = 40 self.offsete = 40 # 能量最大值 self.max_en = 20000 # 初始状态为静音 self.status = 0 self.count = 0 self.silence = 0 self.frame_len = 256 self.frame_inc = 128 self.cur_status = 0 self.frames = [] # 数据开始偏移 self.frames_start = [] self.frames_start_num = 0 # 数据结束偏移 self.frames_end = [] self.frames_end_num = 0 # 缓存数据 self.cache_frames = [] self.cache = "" # 最大缓存长度 self.cache_frames_num = 0 self.end_flag = False self.wait_flag = False self.on = True self.callback = None self.callback_res = [] self.callback_kwargs = {} def clean(self): self.frames = [] # 数据开始偏移 self.frames_start = [] self.frames_start_num = 0 # 数据结束偏移 self.frames_end = [] self.frames_end_num = 0 # 缓存数据 self.cache_frames = [] # 最大缓存长度 self.cache_frames_num = 0 self.end_flag = False self.wait_flag = False def go(self): self.wait_flag = False def wait(self): self.wait_flag = True def stop(self): self.on = False def add(self, frame, wait=True): if wait: print 'wait' frame = self.cache + frame while len(frame) > self.frame_len: frame_block = frame[:self.frame_len] self.cache_frames.append(frame_block) frame = frame[self.frame_len:] if wait: self.cache = frame else: self.cache = "" self.cache_frames.append(-1) def run(self,hasNum): print "开始执行音频端点检测" step = self.frame_len - self.frame_inc num = 0 while 1: # 开始端点 # 获得音频文件数字信号 if self.wait_flag: sleep(1) continue if len(self.cache_frames) < 2: sleep(0.05) continue if self.cache_frames[1] == -1: print '----------------没有声音--------------' break # 从缓存中读取音频数据 record_stream = "".join(self.cache_frames[:2]) wave_data = np.fromstring(record_stream, dtype=np.int16) wave_data = wave_data * 1.0 / self.max_en data = wave_data[np.arange(0, self.frame_len)] speech_data = self.cache_frames.pop(0) # 获得音频过零率 zcr = ZCR(data) # 获得音频的短时能量, 平方放大 amp = STE(data) ** 2 # 返回当前音频数据状态 res = self.speech_status(amp, zcr) if res == 2: hasNum += 1 if hasNum > 10: print '+++++++++++++++++++++++++有声音++++++++++++++++++++++++' break num = num + 1 # 一段一段进行检测 self.frames_start.append(speech_data) self.frames_start_num += 1 if self.frames_start_num == self.offsets: # 开始音频开始的缓存部分 self.frames_start.pop(0) self.frames_start_num -= 1 if self.end_flag: # 当音频结束后进行后部缓存 self.frames_end_num += 1 # 下一段语音开始，或达到缓存阀值 if res == 2 or self.frames_end_num == self.offsete: speech_stream = b"".join(self.frames + self.frames_end) self.callback_res.append(self.callback(speech_stream, **self.callback_kwargs)) # 数据环境初始化 # self.clean() self.end_flag = False self.frames = [] self.frames_end_num = 0 self.frames_end = [] self.frames_end.append(speech_data) if res == 2: if self.cur_status in [0, 1]: # 添加开始偏移数据到数据缓存 self.frames.append(b"".join(self.frames_start)) # 添加当前的语音数据 self.frames.append(speech_data) if res == 3: print '检测音频结束' self.frames.append(speech_data) # 开启音频结束标志 self.end_flag = True self.cur_status = res # return self.callback_res def speech_status(self, amp, zcr): status = 0 # 0= 静音， 1= 可能开始, 2=确定进入语音段 if self.cur_status in [0, 1]: # 确定进入语音段 if amp > self.amp1: status = 2 self.silence = 0 self.count += 1 # 可能处于语音段 elif amp > self.amp2 or zcr > self.zcr2: status = 1 self.count += 1 # 静音状态 else: status = 0 self.count = 0 self.count = 0 # 2 = 语音段 elif self.cur_status == 2: # 保持在语音段 if amp > self.amp2 or zcr > self.zcr2: self.count += 1 status = 2 # 语音将结束 else: # 静音还不够长，尚未结束 self.silence += 1 if self.silence < self.maxsilence: self.count += 1 status = 2 # 语音长度太短认为是噪声 elif self.count < self.minlen: status = 0 self.silence = 0 self.count = 0 # 语音结束 else: status = 3 self.silence = 0 self.count = 0 return status def read_file_data(filename): """ 输入:需要读取的文件名 返回:（声道，量化位数，采样率，数据) """ read_file = wave.open(filename, "r") params = read_file.getparams() nchannels, sampwidth, framerate, nframes = params[:4] data = read_file.readframes(nframes) return nchannels, sampwidth, framerate, data class FileParser(Vad): def __init__(self): self.block_size = 256 Vad.__init__(self) def read_file(self, filename): if not os.path.isfile(filename): print "文件%s不存在" % filename return FAIL datas = read_file_data(filename)[-1] self.add(datas, False) if __name__ == "__main__": stream_test = FileParser() filename = 'test1566606924822.wav' result = stream_test.read_file(filename) if result != FAIL: stream_test.run(0)
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