Python開發之路（6）— 綜郃心知天氣、語言喚醒和百度API做一個語音天氣助手

#!/usr/bin/env pythonimportcollections importpyaudio importsnowboydetect importtime importwave importos importlogging fromctypesimport*fromcontextlibimportcontextmanager logging.basicConfig() logger=logging.getLogger('snowboy') logger.setLevel(logging.INFO) TOP_DIR=os.path.dirname(os.path.abspath(__file__)) RESOURCE_FILE=os.path.join(TOP_DIR,'resources/common.res') DETECT_DING=os.path.join(TOP_DIR,'resources/ding.wav') DETECT_DONG=os.path.join(TOP_DIR,'resources/dong.wav')defpy_error_handler(filename,line,function,err,fmt):pass ERROR_HANDLER_FUNC=CFUNCTYPE(None,c_char_p,c_int,c_char_p,c_int,c_char_p) c_error_handler=ERROR_HANDLER_FUNC(py_error_handler) @contextmanager defno_alsa_error():try: asound =cdll.LoadLibrary('libasound.so') asound.snd_lib_error_set_handler(c_error_handler)yield asound.snd_lib_error_set_handler(None)except:yieldpassclassRingBuffer(object):'''Ring buffer to hold audio from PortAudio'''def__init__(self,size=4096): self._buf=collections.deque(maxlen=size)defextend(self,data):'''Adds data to the end of buffer''' self._buf.extend(data)defget(self):'''Retrieves data from the beginning of buffer and clears it''' tmp =bytes(bytearray(self._buf)) self._buf.clear()returntmp defplay_audio_file(fname=DETECT_DONG):'''Simple callback function to play a wave file. By default it plays a Ding sound. :param str fname: wave file name :return: None '''ding_wav=wave.open(fname,'rb') ding_data =ding_wav.readframes(ding_wav.getnframes())withno_alsa_error(): audio =pyaudio.PyAudio() stream_out =audio.open(format=audio.get_format_from_width(ding_wav.getsampwidth()), channels=ding_wav.getnchannels(), rate=ding_wav.getframerate(),input=False,output=True) stream_out.start_stream() stream_out.write(ding_data) time.sleep(0.2) stream_out.stop_stream() stream_out.close() audio.terminate()classHotwordDetector(object):''' Snowboy decoder to detect whether a keyword specified by `decoder_model` exists in a microphone input stream. :param decoder_model: decoder model file path, a string or a list of strings :param resource: resource file path. :param sensitivity: decoder sensitivity, a float of a list of floats. The bigger the value, the more senstive the decoder. If an empty list is provided, then the default sensitivity in the model will be used. :param audio_gain: multiply input volume by this factor. :param apply_frontend: applies the frontend processing algorithm if True. '''def__init__(self,decoder_model, resource=RESOURCE_FILE,sensitivity=[], audio_gain=1, apply_frontend=False): tm =type(decoder_model) ts =type(sensitivity)iftmisnotlist: decoder_model =[decoder_model]iftsisnotlist: sensitivity =[sensitivity] model_str =','.join(decoder_model) self.detector=snowboydetect.SnowboyDetect( resource_filename=resource.encode(),model_str=model_str.encode()) self.detector.SetAudioGain(audio_gain) self.detector.ApplyFrontend(apply_frontend) self.num_hotwords=self.detector.NumHotwords()iflen(decoder_model)>1andlen(sensitivity)==1: sensitivity =sensitivity*self.num_hotwords iflen(sensitivity)!=0:assertself.num_hotwords==len(sensitivity),'number of hotwords in decoder_model (%d) and sensitivity ''(%d) does not match'%(self.num_hotwords,len(sensitivity)) sensitivity_str =','.join([str(t)fortinsensitivity])iflen(sensitivity)!=0: self.detector.SetSensitivity(sensitivity_str.encode()) self.ring_buffer=RingBuffer( self.detector.NumChannels()*self.detector.SampleRate()*5)# 1、新建一個PyAudio對象 withno_alsa_error(): self.audio=pyaudio.PyAudio()defstart(self,detected_callback=play_audio_file, interrupt_check=lambda:False, sleep_time=0.03, audio_recorder_callback=None, silent_count_threshold=15, recording_timeout=100):''' Start the voice detector. For every `sleep_time` second it checks the audio buffer for triggering keywords. If detected, then call corresponding function in `detected_callback`, which can be a single function (single model) or a list of callback functions (multiple models). Every loop it also calls `interrupt_check` -- if it returns True, then breaks from the loop and return. :param detected_callback: a function or list of functions. The number of items must match the number of models in `decoder_model`. :param interrupt_check: a function that returns True if the main loop needs to stop. :param float sleep_time: how much time in second every loop waits. :param audio_recorder_callback: if specified, this will be called after a keyword has been spoken and after the phrase immediately after the keyword has been recorded. The function will be passed the name of the file where the phrase was recorded. :param silent_count_threshold: indicates how long silence must be heard to mark the end of a phrase that is being recorded. :param recording_timeout: limits the maximum length of a recording. :return: None ''' self._running=Truedefaudio_callback(in_data,frame_count,time_info,status): self.ring_buffer.extend(in_data) play_data =chr(0)*len(in_data)returnplay_data,pyaudio.paContinue # 2、打開聲卡 self.stream_in=self.audio.open(input=True,output=True,format=self.audio.get_format_from_width( self.detector.BitsPerSample()/8), channels=self.detector.NumChannels(), rate=self.detector.SampleRate(), frames_per_buffer=2048, stream_callback=audio_callback)# 3、打開聲卡後，打印一行提示信息print('I am Listening......')# print('**************channels:',self.detector.NumChannels())# print('**************format:',self.audio.get_format_from_width(self.detector.BitsPerSample() / 8))# print('**************rate:',self.detector.SampleRate())ifinterrupt_check(): logger.debug('detect voice return')return tc =type(detected_callback)iftcisnotlist: detected_callback =[detected_callback]iflen(detected_callback)==1andself.num_hotwords>1: detected_callback *=self.num_hotwords assertself.num_hotwords==len(detected_callback),'Error: hotwords in your models (%d) do not match the number of ''callbacks (%d)'%(self.num_hotwords,len(detected_callback)) logger.debug('detecting...') state ='PASSIVE'whileself._runningisTrue:ifinterrupt_check(): logger.debug('detect voice break')break data =self.ring_buffer.get()iflen(data)==0: time.sleep(sleep_time)continue status =self.detector.RunDetection(data)ifstatus==-1: logger.warning('Error initializing streams or reading audio data')#small state machine to handle recording of phrase after keywordifstate=='PASSIVE':ifstatus>0:#key word found self.recordedData=[] self.recordedData.append(data) silentCount =0 recordingCount =0 message ='Keyword 'str(status)' detected at time: ' message =time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())) logger.info(message) callback =detected_callback[status-1]ifcallbackisnotNone: callback()ifaudio_recorder_callbackisnotNone: state ='ACTIVE'continueelifstate=='ACTIVE': stopRecording =FalseifrecordingCount>recording_timeout: stopRecording =Trueelifstatus==-2:#silence foundifsilentCount>silent_count_threshold: stopRecording =Trueelse: silentCount =silentCount1elifstatus==0:#voice found silentCount =0ifstopRecording==True: fname =self.saveMessage() audio_recorder_callback(fname) state ='PASSIVE'continue recordingCount =recordingCount1 self.recordedData.append(data) logger.debug('finished.')defsaveMessage(self):''' Save the message stored in self.recordedData to a timestamped file. ''' filename ='output'str(int(time.time()))'.wav' data =b''.join(self.recordedData)#use wave to save data wf =wave.open(filename,'wb') wf.setnchannels(1) wf.setsampwidth(self.audio.get_sample_size( self.audio.get_format_from_width( self.detector.BitsPerSample()/8))) wf.setframerate(self.detector.SampleRate()) wf.writeframes(data) wf.close() logger.debug('finished saving: 'filename)returnfilename defterminate(self):''' Terminate audio stream. Users can call start() again to detect. :return: None ''' self.stream_in.stop_stream() self.stream_in.close()# self.audio.terminate() self._running=False