python——判断一段音频是否有声音

根据一段wav音频判断该音频是否有声音

#-*- coding: utf-8 -*-import osimport wavefrom time import sleepimport numpy as npSUCCESS = 0FAIL = 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 zcrdef STE(curFrame):    # 短时能量    amp = np.sum(np.abs(curFrame))    return ampclass 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 statusdef 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, dataclass 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 = 'sf_id001_2017-01-11_10_53_56.wav'    result = stream_test.read_file(filename)    if result != FAIL:        stream_test.run(0)

参考：https://github.com/halleytl/pyvad/blob/master/vad.py