def main(input_uri, encoding, sample_rate, language_code='en-US'):
service = cloud_speech.beta_create_Speech_stub(
make_channel('speech.googleapis.com', 443))
# The method and parameters can be inferred from the proto from which the
# grpc client lib was generated. See:
# https://github.com/googleapis/googleapis/blob/master/google/cloud/speech/v1beta1/cloud_speech.proto
response = service.SyncRecognize(cloud_speech.SyncRecognizeRequest(
config=cloud_speech.RecognitionConfig(
# There are a bunch of config options you can specify. See
# https://goo.gl/KPZn97 for the full list.
encoding=encoding, # one of LINEAR16, FLAC, MULAW, AMR, AMR_WB
sample_rate=sample_rate, # the rate in hertz
# See https://g.co/cloud/speech/docs/languages for a list of
# supported languages.
language_code=language_code, # a BCP-47 language tag
),
audio=cloud_speech.RecognitionAudio(
uri=input_uri,
)
), DEADLINE_SECS)
# Print the recognition result alternatives and confidence scores.
for result in response.results:
print('Result:')
for alternative in result.alternatives:
print(u' ({}): {}'.format(
alternative.confidence, alternative.transcript))
def main(input_uri, encoding, sample_rate, language_code='en-US'):
service = cloud_speech.beta_create_Speech_stub(
make_channel('speech.googleapis.com', 443))
# The method and parameters can be inferred from the proto from which the
# grpc client lib was generated. See:
# https://github.com/googleapis/googleapis/blob/master/google/cloud/speech/v1beta1/cloud_speech.proto
response = service.SyncRecognize(
cloud_speech.SyncRecognizeRequest(
config=cloud_speech.RecognitionConfig(
# There are a bunch of config options you can specify. See
# https://goo.gl/KPZn97 for the full list.
encoding=encoding, # one of LINEAR16, FLAC, MULAW, AMR, AMR_WB
sample_rate=sample_rate, # the rate in hertz
# See https://g.co/cloud/speech/docs/languages for a list of
# supported languages.
language_code=language_code, # a BCP-47 language tag
),
audio=cloud_speech.RecognitionAudio(uri=input_uri, )),
DEADLINE_SECS)
# Print the recognition result alternatives and confidence scores.
for result in response.results:
print('Result:')
for alternative in result.alternatives:
print(u' ({}): {}'.format(alternative.confidence,
alternative.transcript))
def main():
with cloud_speech.beta_create_Speech_stub(
make_channel('speech.googleapis.com', 443)) as service:
# stoprequest is event object which is set in `listen_print_loop`
# to indicate that the trancsription should be stopped.
#
# The `_fill_buffer` thread checks this object, and closes
# the `audio_stream` once it's set.
stoprequest = threading.Event()
# For streaming audio from the microphone, there are three threads.
# First, a thread that collects audio data as it comes in
with record_audio(RATE, CHUNK, stoprequest) as buffered_audio_data:
# Second, a thread that sends requests with that data
requests = request_stream(buffered_audio_data, RATE)
# Third, a thread that listens for transcription responses
recognize_stream = service.StreamingRecognize(
requests, DEADLINE_SECS)
# Exit things cleanly on interrupt
signal.signal(signal.SIGINT, lambda *_: recognize_stream.cancel())
# Now, put the transcription responses to use.
try:
listen_print_loop(recognize_stream, stoprequest)
recognize_stream.cancel()
except face.CancellationError:
# This happens because of the interrupt handler
pass
def run_recognition_loop():
global frames
global silent_frames
global is_recording
global should_finish_stream
if len(silent_frames) > 4:
silent_frames = silent_frames[-4:]
while not is_recording:
time.sleep(args.frame_seconds // 4)
if len(frames) > 4:
for frame_index in range(4):
data = frames[frame_index]
rms = audioop.rms(data, 2)
decibel = 20 * math.log10(rms) if rms > 0 else 0
if decibel < args.silent_decibel:
silent_frames += frames[0:frame_index+1]
del frames[0:frame_index + 1]
return
is_recording = True
frames = silent_frames + frames
silent_frames = []
with cloud_speech_pb2.beta_create_Speech_stub(make_channel(args.host, args.ssl_port)) as service:
try:
listen_loop(service.StreamingRecognize(request_stream(), args.deadline_seconds))
printr(" ".join((bold(recognition_result.transcription), " ", "confidence: ", str(int(recognition_result.confidence * 100)), "%")))
print()
except Exception as e:
print(str(e))
def run_recognition_loop():
global frames
global silent_frames
global is_recording
global should_finish_stream
if len(silent_frames) > 4:
silent_frames = silent_frames[-4:]
#print ("silent_frames:",silent_frames)
while not is_recording:
#print("---sleep---")
time.sleep(args.frame_seconds // 4) #処理を一時停止する
#print("----on-----")
#なんのif文かわからん
if len(frames) > 2:
for frame_index in range(4):
data = frames[frame_index]
rms = audioop.rms(data, 2)
decibel = 20 * math.log10(rms) if rms > 0 else 0
if decibel < args.silent_decibel:
silent_frames += frames[0:frame_index + 1]
del frames[0:frame_index + 1] #リストの部分を削除
return
is_recording = True
frames = silent_frames + frames
silent_frames = []
#音声をテキストにする
with cloud_speech_pb2.beta_create_Speech_stub(
make_channel(args.host,
args.ssl_port)) as service: #このフォルダをservice関数に入れる
try:
#ここで録音して変換している
print("処理中")
listen_loop(
service.StreamingRecognize(request_stream(),
args.deadline_seconds))
#print("service:",service.StreamingRecognize(request_stream(), args.deadline_seconds))
#最終的な結果はここ
printr(" ".join((bold(recognition_result.transcription)))) #" ",
#"confidence: ", str(int(recognition_result.confidence * 100)), "%",
#"time: ",time.strftime("%H:%M:%S"))))
list = {
"ID": ID,
"trans": recognition_result.transcription,
"confidence": recognition_result.confidence * 100,
"time": time.strftime("%H:%M:%S"),
"finish": finish
}
json_data = json.dumps(list)
response = requests.post(
'https://2dhdoj4j8c.execute-api.ap-northeast-1.amazonaws.com:443/dev/datadump',
json_data)
#pprint.pprint(response.json())
print()
except Exception as e:
print(str(e))
def main():
stop_audio = threading.Event()
with cloud_speech.beta_create_Speech_stub(make_channel("speech.googleapis.com", 443)) as service:
try:
listen_print_loop(service.StreamingRecognize(request_stream(stop_audio), DEADLINE_SECS))
finally:
# Stop the request stream once we're done with the loop - otherwise
# it'll keep going in the thread that the grpc lib makes for it..
stop_audio.set()
def threaded_listen():
with cloud_speech.beta_create_Speech_stub(self.google_grpc_channel('speech.googleapis.com', 443)) as service:
with source as s:
while self._running_voice:
try: # listen for 1 second, then check again if the stop function has been called
init_buff = self.listen_trigger(s, 1)
except WaitTimeoutError: # listening timed out, just try again
pass
else:
self.g_stream_loop(service, source, init_buff, callback)
def main():
stop_audio = threading.Event()
with cloud_speech.beta_create_Speech_stub(
make_channel('speech.googleapis.com', 443)) as service:
try:
listen_print_loop(
service.StreamingRecognize(request_stream(stop_audio),
DEADLINE_SECS))
finally:
# Stop the request stream once we're done with the loop - otherwise
# it'll keep going in the thread that the grpc lib makes for it..
stop_audio.set()
def __init__(self):
self.pub_transcript = rospy.Publisher('result_transcript', ResultTranscript, queue_size=5)
self.pub_start_speech = rospy.Publisher('start_of_speech', Empty, queue_size=10)
self.pub_end_speech = rospy.Publisher('end_of_speech', Empty, queue_size=10)
self.is_start_audio = False
self.is_start_speech = False
self.is_stop_audio = True
self.stop_audio = threading.Event()
with cloud_speech.beta_create_Speech_stub(self.make_channel('speech.googleapis.com', 443)) as self.service:
self.t1 = threading.Thread(target=self.listen_print_loop)
self.t1.start()
def main(input_uri, encoding, sample_rate, language_code='en-US'):
channel = make_channel('speech.googleapis.com', 443)
service = cloud_speech_pb2.beta_create_Speech_stub(channel)
# The method and parameters can be inferred from the proto from which the
# grpc client lib was generated. See:
# https://github.com/googleapis/googleapis/blob/master/google/cloud/speech/v1beta1/cloud_speech.proto
operation = service.AsyncRecognize(cloud_speech_pb2.AsyncRecognizeRequest(
config=cloud_speech_pb2.RecognitionConfig(
# There are a bunch of config options you can specify. See
# https://goo.gl/KPZn97 for the full list.
encoding=encoding, # one of LINEAR16, FLAC, MULAW, AMR, AMR_WB
sample_rate=sample_rate, # the rate in hertz
# See https://g.co/cloud/speech/docs/languages for a list of
# supported languages.
language_code=language_code, # a BCP-47 language tag
),
audio=cloud_speech_pb2.RecognitionAudio(
uri=input_uri,
)
), DEADLINE_SECS)
# Print the longrunning operation handle.
print(operation)
# Construct a long running operation endpoint.
service = operations_grpc_pb2.beta_create_Operations_stub(channel)
name = operation.name
while True:
# Give the server a few seconds to process.
print('Waiting for server processing...')
time.sleep(1)
operation = service.GetOperation(
operations_grpc_pb2.GetOperationRequest(name=name),
DEADLINE_SECS)
if operation.done:
break
response = cloud_speech_pb2.AsyncRecognizeResponse()
operation.response.Unpack(response)
# Print the recognition result alternatives and confidence scores.
for result in response.results:
print('Result:')
for alternative in result.alternatives:
print(u' ({}): {}'.format(
alternative.confidence, alternative.transcript))
def main(input_uri, encoding, sample_rate):
channel = make_channel('speech.googleapis.com', 443)
service = cloud_speech_pb2.beta_create_Speech_stub(channel)
# The method and parameters can be inferred from the proto from which the
# grpc client lib was generated. See:
# https://github.com/googleapis/googleapis/blob/master/google/cloud/speech/v1beta1/cloud_speech.proto
response = service.AsyncRecognize(cloud_speech_pb2.AsyncRecognizeRequest(
config=cloud_speech_pb2.RecognitionConfig(
# There are a bunch of config options you can specify. See
# https://goo.gl/KPZn97 for the full list.
encoding=encoding, # one of LINEAR16, FLAC, MULAW, AMR, AMR_WB
sample_rate=sample_rate, # the rate in hertz
# See
# https://g.co/cloud/speech/docs/best-practices#language_support
# for a list of supported languages.
language_code='fi-FI', # a BCP-47 language tag
),
audio=cloud_speech_pb2.RecognitionAudio(
uri=input_uri,
)
), DEADLINE_SECS)
# Print the longrunning operation handle.
print >> sys.stderr, response
# Construct a long running operation endpoint.
service = operations_grpc_pb2.beta_create_Operations_stub(channel)
name = response.name
while True:
# Give the server a few seconds to process.
print >> sys.stderr, 'Waiting for server processing...'
time.sleep(1)
# Get the long running operation with response.
response = service.GetOperation(
operations_grpc_pb2.GetOperationRequest(name=name),
DEADLINE_SECS)
if response.done:
break
# Print the recognition results.
results = cloud_speech_pb2.AsyncRecognizeResponse()
response.response.Unpack(results)
for result in results.results:
for alternative in result.alternatives:
print(('"{}",{}').format(alternative.transcript.encode('utf-8'), alternative.confidence))
def main(input_uri, encoding, sample_rate):
service = cloud_speech.beta_create_Speech_stub(
make_channel('speech.googleapis.com', 443))
# The method and parameters can be inferred from the proto from which the
# grpc client lib was generated. See:
# https://github.com/googleapis/googleapis/blob/master/google/cloud/speech/v1beta1/cloud_speech.proto
response = service.SyncRecognize(
cloud_speech.SyncRecognizeRequest(
config=cloud_speech.RecognitionConfig(
encoding=encoding,
sample_rate=sample_rate,
),
audio=cloud_speech.RecognitionAudio(uri=input_uri, )),
DEADLINE_SECS)
# Print the recognition results.
print(response.results)
def main(input_uri, encoding, sample_rate, language_code='en-US'):
channel = make_channel('speech.googleapis.com', 443)
service = cloud_speech_pb2.beta_create_Speech_stub(channel)
# The method and parameters can be inferred from the proto from which the
# grpc client lib was generated. See:
# https://github.com/googleapis/googleapis/blob/master/google/cloud/speech/v1beta1/cloud_speech.proto
operation = service.AsyncRecognize(
cloud_speech_pb2.AsyncRecognizeRequest(
config=cloud_speech_pb2.RecognitionConfig(
# There are a bunch of config options you can specify. See
# https://goo.gl/KPZn97 for the full list.
encoding=encoding, # one of LINEAR16, FLAC, MULAW, AMR, AMR_WB
sample_rate=sample_rate, # the rate in hertz
# See https://g.co/cloud/speech/docs/languages for a list of
# supported languages.
language_code=language_code, # a BCP-47 language tag
),
audio=cloud_speech_pb2.RecognitionAudio(uri=input_uri, )),
DEADLINE_SECS)
# Print the longrunning operation handle.
print(operation)
# Construct a long running operation endpoint.
service = operations_grpc_pb2.beta_create_Operations_stub(channel)
name = operation.name
while True:
# Give the server a few seconds to process.
print('Waiting for server processing...')
time.sleep(1)
operation = service.GetOperation(
operations_grpc_pb2.GetOperationRequest(name=name), DEADLINE_SECS)
if operation.done:
break
response = cloud_speech_pb2.AsyncRecognizeResponse()
operation.response.Unpack(response)
# Print the recognition result alternatives and confidence scores.
for result in response.results:
print('Result:')
for alternative in result.alternatives:
print(u' ({}): {}'.format(alternative.confidence,
alternative.transcript))
def main(input_uri, encoding, sample_rate):
service = cloud_speech.beta_create_Speech_stub(
make_channel('speech.googleapis.com', 443))
# The method and parameters can be inferred from the proto from which the
# grpc client lib was generated. See:
# https://github.com/googleapis/googleapis/blob/master/google/cloud/speech/v1beta1/cloud_speech.proto
response = service.SyncRecognize(cloud_speech.SyncRecognizeRequest(
config=cloud_speech.RecognitionConfig(
encoding=encoding,
sample_rate=sample_rate,
),
audio=cloud_speech.RecognitionAudio(
uri=input_uri,
)
), DEADLINE_SECS)
# Print the recognition results.
print(response.results)
def main():
#メイン部分
global queue #列
global should_finish_stream
preloading_process = Process(target=reading_audio_loop, args=[queue])
preloading_process.start()
while True:
should_finish_stream = False
with cloud_speech_pb2.beta_create_Speech_stub(make_channel(args.host, args.ssl_port)) as service:
listen_loop(service.StreamingRecognize(request_stream(), args.deadline_seconds))
if recognition_result.success:
printr(" ".join((bold(recognition_result.transcription), " ", "confidence: ", str(int(recognition_result.confidence * 100)), "%")))
print()
def main(input_uri, encoding, sample_rate):
channel = make_channel('speech.googleapis.com', 443)
service = cloud_speech_pb2.beta_create_Speech_stub(channel)
# The method and parameters can be inferred from the proto from which the
# grpc client lib was generated. See:
# https://github.com/googleapis/googleapis/blob/master/google/cloud/speech/v1beta1/cloud_speech.proto
response = service.AsyncRecognize(cloud_speech_pb2.AsyncRecognizeRequest(
config=cloud_speech_pb2.RecognitionConfig(
# There are a bunch of config options you can specify. See
# https://goo.gl/A6xv5G for the full list.
encoding=encoding, # one of LINEAR16, FLAC, MULAW, AMR, AMR_WB
sample_rate=sample_rate, # the rate in hertz
# See
# https://g.co/cloud/speech/docs/best-practices#language_support
# for a list of supported languages.
language_code='en-US', # a BCP-47 language tag
),
audio=cloud_speech_pb2.RecognitionAudio(
uri=input_uri,
)
), DEADLINE_SECS)
# Print the longrunning operation handle.
print(response)
# Construct a long running operation endpoint.
service = operations_grpc_pb2.beta_create_Operations_stub(channel)
name = response.name
while True:
# Give the server a few seconds to process.
print('Waiting for server processing...')
time.sleep(1)
# Get the long running operation with response.
response = service.GetOperation(
operations_grpc_pb2.GetOperationRequest(name=name),
DEADLINE_SECS)
if response.done:
break
# Print the recognition results.
results = cloud_speech_pb2.AsyncRecognizeResponse()
response.response.Unpack(results)
print(results)
def run_recognition_loop(self):
print("===start recognition")
#if len(self.silent_frames) > 4:
# self.silent_frames = self.silent_frames[-4:]
#変換を依頼している時には、
#while not self.is_recording:
while not self.should_finish_stream :
#print(sys._getframe().f_code.co_name)
time.sleep(self.frame_seconds // 4)
if len(self.frames) == 0 :
continue
#音が入ってくるまで、解析処理を行わないようにする。
data = self.frames[0]
rms = audioop.rms(data, 2)
decibel = 20 * math.log10(rms) if rms > 0 else 0
#print("decibel", decibel)
#音が入ってくるまで、処理を行わない。
if decibel < self.silent_decibel:
#print("pre frame len",len(self.frames))
if len(self.frames) > 0 :
self.frames.pop(0)
continue
print(sys._getframe().f_code.co_name, "get sound. decibel=",decibel)
self.is_recording = True
self.frames = self.silent_frames + self.frames
with cloud_speech_pb2.beta_create_Speech_stub(self.make_channel(self.host, self.ssl_port)) as service:
try:
self.listen_loop(service.StreamingRecognize(self.request_stream(), self.deadline_seconds))
#処理結果が終了した時だけ出力するようにした
if self.recognition_result.is_final :
printr(" ".join((bold(self.recognition_result.transcription), " ", "confidence: ", str(int(self.recognition_result.confidence * 100)), "%")))
self.recognition_result.is_final = False
#with open('result.txt', 'w') as f:
# f.write(recognition_result.transcription)
except Exception as e:
print(str(e))
def main(input_uri, encoding, sample_rate):
channel = make_channel('speech.googleapis.com', 443)
service = cloud_speech_pb2.beta_create_Speech_stub(channel)
# The method and parameters can be inferred from the proto from which the
# grpc client lib was generated. See:
# https://github.com/googleapis/googleapis/blob/master/google/cloud/speech/v1beta1/cloud_speech.proto
response = service.AsyncRecognize(cloud_speech_pb2.AsyncRecognizeRequest(
config=cloud_speech_pb2.RecognitionConfig(
encoding=encoding,
sample_rate=sample_rate,
),
audio=cloud_speech_pb2.RecognitionAudio(
uri=input_uri,
)
), DEADLINE_SECS)
# Print the longrunning operation handle.
print(response)
# Construct a long running operation endpoint.
service = operations_grpc_pb2.beta_create_Operations_stub(channel)
name = response.name
while True:
# Give the server a few seconds to process.
print('Waiting for server processing...')
time.sleep(1)
# Get the long running operation with response.
response = service.GetOperation(
operations_grpc_pb2.GetOperationRequest(name=name),
DEADLINE_SECS)
if response.done:
break
# Print the recognition results.
results = cloud_speech_pb2.AsyncRecognizeResponse()
response.response.Unpack(results)
print(results)
def main(input_uri, encoding, sample_rate):
service = cloud_speech.beta_create_Speech_stub(
make_channel('speech.googleapis.com', 443))
# The method and parameters can be inferred from the proto from which the
# grpc client lib was generated. See:
# https://github.com/googleapis/googleapis/blob/master/google/cloud/speech/v1beta1/cloud_speech.proto
response = service.SyncRecognize(
cloud_speech.SyncRecognizeRequest(
config=cloud_speech.RecognitionConfig(
# There are a bunch of config options you can specify. See
# https://goo.gl/A6xv5G for the full list.
encoding=encoding, # one of LINEAR16, FLAC, MULAW, AMR, AMR_WB
sample_rate=sample_rate, # the rate in hertz
# See
# https://g.co/cloud/speech/docs/best-practices#language_support
# for a list of supported languages.
language_code='en-US', # a BCP-47 language tag
),
audio=cloud_speech.RecognitionAudio(uri=input_uri, )),
DEADLINE_SECS)
# Print the recognition results.
print(response.results)
def main(input_uri, encoding, sample_rate):
channel = make_channel('speech.googleapis.com', 443)
service = cloud_speech_pb2.beta_create_Speech_stub(channel)
# The method and parameters can be inferred from the proto from which the
# grpc client lib was generated. See:
# https://github.com/googleapis/googleapis/blob/master/google/cloud/speech/v1beta1/cloud_speech.proto
response = service.AsyncRecognize(
cloud_speech_pb2.AsyncRecognizeRequest(
config=cloud_speech_pb2.RecognitionConfig(
encoding=encoding,
sample_rate=sample_rate,
),
audio=cloud_speech_pb2.RecognitionAudio(uri=input_uri, )),
DEADLINE_SECS)
# Print the longrunning operation handle.
print(response)
# Construct a long running operation endpoint.
service = operations_grpc_pb2.beta_create_Operations_stub(channel)
name = response.name
while True:
# Give the server a few seconds to process.
print('Waiting for server processing...')
time.sleep(1)
# Get the long running operation with response.
response = service.GetOperation(
operations_grpc_pb2.GetOperationRequest(name=name), DEADLINE_SECS)
if response.done:
break
# Print the recognition results.
results = cloud_speech_pb2.AsyncRecognizeResponse()
response.response.Unpack(results)
print(results)
def main():
with cloud_speech.beta_create_Speech_stub(
make_channel('speech.googleapis.com', 443)) as service:
# For streaming audio from the microphone, there are three threads.
# First, a thread that collects audio data as it comes in
with record_audio(RATE, CHUNK) as buffered_audio_data:
# Second, a thread that sends requests with that data
requests = request_stream(buffered_audio_data, RATE)
# Third, a thread that listens for transcription responses
recognize_stream = service.StreamingRecognize(
requests, DEADLINE_SECS)
# Exit things cleanly on interrupt
signal.signal(signal.SIGINT, lambda *_: recognize_stream.cancel())
# Now, put the transcription responses to use.
try:
listen_print_loop(recognize_stream)
recognize_stream.cancel()
except face.CancellationError:
# This happens because of the interrupt handler
pass
def main():
with cloud_speech.beta_create_Speech_stub(
make_channel('speech.googleapis.com', 443)) as service:
# For streaming audio from the microphone, there are three threads.
# First, a thread that collects audio data as it comes in
with record_audio(RATE, CHUNK) as buffered_audio_data:
# Second, a thread that sends requests with that data
requests = request_stream(buffered_audio_data, RATE)
# Third, a thread that listens for transcription responses
recognize_stream = service.StreamingRecognize(
requests, DEADLINE_SECS)
# Exit things cleanly on interrupt
signal.signal(signal.SIGINT, lambda *_: recognize_stream.cancel())
# Now, put the transcription responses to use.
try:
listen_print_loop(recognize_stream)
recognize_stream.cancel()
except face.CancellationError:
# This happens because of the interrupt handler
pass
def main(input_uri, encoding, sample_rate):
service = cloud_speech.beta_create_Speech_stub(
make_channel('speech.googleapis.com', 443))
# The method and parameters can be inferred from the proto from which the
# grpc client lib was generated. See:
# https://github.com/googleapis/googleapis/blob/master/google/cloud/speech/v1beta1/cloud_speech.proto
response = service.SyncRecognize(cloud_speech.SyncRecognizeRequest(
config=cloud_speech.RecognitionConfig(
# There are a bunch of config options you can specify. See
# https://goo.gl/A6xv5G for the full list.
encoding=encoding, # one of LINEAR16, FLAC, MULAW, AMR, AMR_WB
sample_rate=sample_rate, # the rate in hertz
# See
# https://g.co/cloud/speech/docs/best-practices#language_support
# for a list of supported languages.
language_code='en-US', # a BCP-47 language tag
),
audio=cloud_speech.RecognitionAudio(
uri=input_uri,
)
), DEADLINE_SECS)
# Print the recognition results.
print(response.results)
def service(self):
service = cloud_speech.beta_create_Speech_stub(self.channel)
return service
# 音量が閾値より小さかったら，データを捨てループを抜ける ----
if decibel < DECIBEL_THRESHOLD:
frames_startbuf.append(frames[0:i + 1])
del frames[0:i + 1]
break
# 全フレームの音量が閾値を超えていたら，録音開始！！ ----
# 更に，framesの先頭に，先頭バッファをプラス
# これをしないと「かっぱ」の「かっ」など，促音の前の音が消えてしまう
if i == START_FRAME_LEN - 1:
flag_RecordStart = True
frames = frames_startbuf + frames
# googleサーバに接続 ############################
print "\nconnecting ...."
with cloud_speech.beta_create_Speech_stub(
make_channel('speech.googleapis.com', 443)) as service:
try:
print "success to connect."
except:
print "connection error."
# 録音開始後の処理 ###############################
listen_print_loop(
service.StreamingRecognize(request_stream(), DEADLINE_SECS))
# 音声認識 繰り返しの終了判定 #####################
if re.match(EXIT_WORD, recog_result):
print('Exiting..')
break
# 音声認識繰り返ししない設定 ######################