class Translator:
def __init__(self):
self.client = SpeechClient()
storage_client = storage.Client()
self.bucket_name = 'cross-culture-audios'
self.bucket = storage_client.get_bucket(self.bucket_name)
def translate_long(self, gs_uri):
audio = types.RecognitionAudio(uri=gs_uri, )
config = types.RecognitionConfig(
encoding='FLAC',
language_code='en-US',
sample_rate_hertz=44100,
)
operation = self.client.long_running_recognize(config=config,
audio=audio)
op_result = operation.result()
result = '\n'.join([
str.strip(result.alternatives[0].transcript)
for result in op_result.results if len(result.alternatives) > 0
])
return result
def translate_with_timestamps(self, gs_uri):
audio = types.RecognitionAudio(uri=gs_uri, )
config = types.RecognitionConfig(
encoding='FLAC',
language_code='en-US',
# sample_rate_hertz=44100,
enable_word_time_offsets=True)
operation = self.client.long_running_recognize(config=config,
audio=audio)
results = []
for result in operation.result().results:
alternatives = result.alternatives
if len(alternatives) == 0:
continue
alternative = alternatives[0]
for word_info in alternative.words:
word = word_info.word
start_time = word_info.start_time.seconds + round(
word_info.start_time.nanos * 1e-9, 1)
end_time = word_info.end_time.seconds + round(
word_info.end_time.nanos * 1e-9, 1)
results.append([word, start_time, end_time])
return results
def upload_to_gcs(self, filepath):
filename = ntpath.basename(filepath)
gs_filepath = 'audios/%s' % filename
blob = self.bucket.blob(gs_filepath)
blob.upload_from_filename(filepath)
return self.generate_uri(gs_filepath)
def delete_from_gcs(self, filename):
gs_filepath = 'audios/%s' % filename
self.bucket.delete_blob(gs_filepath)
def generate_uri(self, filepath):
return 'gs://%s/%s' % (self.bucket_name, filepath)
def recognize_audio_from_file(
file: Union[str, os.PathLike],
credential: Union[str, os.PathLike, None] = None,
language_code: str = 'en-US',
encoding: enums.RecognitionConfig.AudioEncoding = enums.RecognitionConfig.
AudioEncoding.FLAC,
sampling_rate_hertz: int = 44100,
) -> types.RecognizeResponse:
"""
Args:
file (str, os.PathLike) :
credential (str) :
language_code (str) :
encoding (str) :
sampling_rate_hertz (int) :
Returns:
types.RecognizeResponse
"""
if credential is None:
client = SpeechClient()
else:
credentials = Credentials.from_service_account_file(
filename=credential)
client = SpeechClient(credentials=credentials)
config = types.RecognitionConfig(encoding=encoding,
language_code=language_code,
sampling_rate_hertz=sampling_rate_hertz)
with io.open(file, 'rb') as audio:
content = audio.read()
audio = types.RecognitionAudio(content=content)
return client.recognize(config, audio)
def __init__(self, credential: Union[str, os.PathLike, None] = None):
"""
Args:
credential (str, os.PathLike, None) :
"""
if credential is None:
self.client = SpeechClient()
else:
credentials = Credentials.from_service_account_file(
filename=credential)
self.client = SpeechClient(credentials=credentials)
def onStart(self): super().onStart() os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = str(self._credentialsFile) self._client = SpeechClient() # noinspection PyUnresolvedReferences config = types.RecognitionConfig( encoding=enums.RecognitionConfig.AudioEncoding.LINEAR16, sample_rate_hertz=self.AudioServer.SAMPLERATE, language_code=self.LanguageManager.getLanguageAndCountryCode() ) self._streamingConfig = types.StreamingRecognitionConfig(config=config, interim_results=True)
def transcribe_gcs(self, gcs_uri):
"""Asynchronously transcribes the audio file specified by the gcs_uri.
args:
gcs_uri - URI with format 'gs://<bucket>/<path_to_audio>'
returns:
trans - a list of transcribed sections
"""
printmsg.begin('Initiating Google Cloud Speech operation')
client = SpeechClient()
audio = types.RecognitionAudio(uri=gcs_uri)
config = types.RecognitionConfig(
encoding=enums.RecognitionConfig.AudioEncoding.FLAC,
sample_rate_hertz=44100,
language_code='en-GB',
enable_word_time_offsets=True)
operation = client.long_running_recognize(config, audio)
printmsg.end()
printmsg.begin('Waiting for operation to complete [0%%]')
while not operation.done():
time.sleep(1)
printmsg.begin('Waiting for operation to complete [%s%%]' %
operation.metadata.progress_percent)
response = operation.result(timeout=10)
printmsg.end()
# Each result is for a consecutive portion of the audio. Iterate through
# them to get the transcripts for the entire audio file.
trans = []
for result in response.results:
# The first alternative is the most likely one for this portion.
best = result.alternatives[0]
get_ts = lambda x: dict(min=x.seconds // 60,
sec=x.seconds % 60,
msec=x.nanos // (10**6))
seg = dict(text=best.transcript,
confidence=best.confidence,
words=[])
# loop the words
for word_info in best.words:
word = word_info.word
start_time = word_info.start_time
end_time = word_info.end_time
word_obj = dict(word=word, tstamp=get_ts(start_time))
seg['words'].append(word_obj)
trans.append(seg)
return trans
def onStart(self):
super().onStart()
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = str(
Path(self.Commons.rootDir(), 'credentials/googlecredentials.json'))
self._client = SpeechClient()
# noinspection PyUnresolvedReferences
config = types.RecognitionConfig(
encoding=enums.RecognitionConfig.AudioEncoding.LINEAR16,
sample_rate_hertz=self.ConfigManager.getAliceConfigByName(
'micSampleRate'),
language_code=self.LanguageManager.activeLanguageAndCountryCode)
self._streamingConfig = types.StreamingRecognitionConfig(
config=config, interim_results=True)
def VoiceRecognition(b_voice_data):
print("VR: initialized")
try:
client = SpeechClient()
print("VR: preparing recognition request")
audio = types.RecognitionAudio(content=b_voice_data)
config = types.RecognitionConfig(
# setup default Telegram format
encoding=enums.RecognitionConfig.AudioEncoding.OGG_OPUS,
sample_rate_hertz=16000,
language_code='en-US',
max_alternatives=0)
# Recognize speech content
print("VR: call for Google Speech API")
try:
response = client.recognize(config, audio)
print("VR: GCS API call finished")
print(response)
if (response.results):
for result in response.results:
rec_voice = result.alternatives[0].transcript
return rec_voice
else:
print("VR: GCS API returned NULL")
rec_voice = "NDVR"
return rec_voice
except Exception as apiClientExpt:
print(
"VR: FATAL ERROR: unhandled exception when calling recognize API"
)
print(apiClientExpt)
return False
except Exception as speechClientExpt:
print(
"VR: FATAL ERROR: unhandled exception when initializing SpeechClient"
)
print(speechClientExpt)
return False
def __init__(self):
global SpeechClient, types, enums, Credentials
from google.cloud.speech import SpeechClient, types, enums
from google.oauth2.service_account import Credentials
super(GoogleCloudStreamingSTT, self).__init__()
# override language with module specific language selection
self.language = self.config.get('lang') or self.lang
credentials = Credentials.from_service_account_info(
self.credential.get('json'))
self.client = SpeechClient(credentials=credentials)
recognition_config = types.RecognitionConfig(
encoding=enums.RecognitionConfig.AudioEncoding.LINEAR16,
sample_rate_hertz=16000,
language_code=self.language,
model='command_and_search',
max_alternatives=1,
)
self.streaming_config = types.StreamingRecognitionConfig(
config=recognition_config,
interim_results=True,
single_utterance=True,
)
def proof_of_concept():
config = RecognitionConfig(encoding=RecognitionConfig.AudioEncoding.FLAC,
language_code="en-UK",
audio_channel_count=2)
audio = RecognitionAudio(uri='gs://general-rodderscode-co-uk/test.flac')
response = SpeechClient().recognize(config=config, audio=audio)
print(response)
def __transcribe_chunk(self, async_iter):
""" Accesses Google Cloud Speech and print the lyrics for each chunk """
frame_rate, encoding, file_path = async_iter
accuracy_chunk_path = append_before_ext(file_path, '-accuracy')
with open(accuracy_chunk_path, 'rb') as audio_content:
content = audio_content.read()
config = self.__get_config(encoding, frame_rate)
audio = types.RecognitionAudio(content=content)
return SpeechClient().recognize(config, audio)
def get_raw(file_name: str, client: speech.SpeechClient) -> str:
"""
Get the raw Speech to text result from Google Cloud API
:param file_name: File name + path
:param client: Google Cloud API Speech client
:return: str JSON encoded response
"""
audio = types.RecognitionAudio(uri=file_name)
config = types.RecognitionConfig(
encoding=enums.RecognitionConfig.AudioEncoding.FLAC,
sample_rate_hertz=44100,
language_code="de-DE",
enable_word_time_offsets=True)
operation = client.long_running_recognize(config, audio)
response = operation.result(timeout=900)
return MessageToJson(response)
def recognize_stream(bytestream: Generator[ByteString, None,
None], client: speech.SpeechClient,
recognition_config: types.RecognitionConfig, q: Queue):
"""Streams transcription of the given audio file."""
requests = (types.StreamingRecognizeRequest(audio_content=chunk)
for chunk in bytestream)
responses = client.streaming_recognize(
get_streaming_recognition_config(recognition_config), requests)
while True:
try:
resp = next(responses)
logger.debug("reading next response; resp.results is {}".format(
resp.results))
except StopIteration:
logger.info("no more responses!")
break
if resp.results:
final = [x for x in resp.results if x.is_final]
if final: q.put(final[0].alternatives[0])
logger.info("exit from recognize_stream!")
return
def recognize_audio_from_uri(
uri: str,
credential: Union[str, os.PathLike, None] = None,
language_code: str = 'en-US',
encoding: enums.RecognitionConfig.AudioEncoding = enums.RecognitionConfig.
AudioEncoding.FLAC,
sampling_rate_hertz: int = 44100,
) -> types.RecognizeResponse:
"""
Args:
uri (str) : Cloud
credential (str, os.PathLike, None) :
language_code:
encoding (enums.RecognitionConfig.AudioEncoding) :
sampling_rate_hertz (int) :
Returns:
types.RecognizeResponse
"""
if credential is None:
client = SpeechClient()
else:
credentials = Credentials.from_service_account_file(
filename=credential)
client = SpeechClient(credentials=credentials)
config = types.RecognitionConfig(encoding=encoding,
language_code=language_code,
sample_rate_hertz=sampling_rate_hertz)
audio = types.RecognitionAudio(uri=uri)
try:
result = client.recognize(config=config, audio=audio)
except exceptions.InvalidArgument:
print(
'cannot synchronize recognition. switched asynchronized recognition'
)
operartion = client.long_running_recognize(config=config, audio=audio)
result = operartion.result()
return result
from flask import Flask, request, render_template
from google.cloud.speech import enums, types, SpeechClient
import json
import os
import traceback
from parse_command import parse_command
app = Flask(__name__)
os.environ.setdefault('GOOGLE_APPLICATION_CREDENTIALS', 'key.json')
client = SpeechClient()
@app.route('/upload', methods=['POST'])
def upload():
raw_audio = request.files['audio_data']
user_agent = request.headers.get('User-Agent')
content = raw_audio.read()
audio = types.RecognitionAudio(content=content)
config = types.RecognitionConfig(
encoding=enums.RecognitionConfig.AudioEncoding.LINEAR16,
audio_channel_count=2,
language_code='en-US',
)
response = client.recognize(config, audio)
print(response)
for result in response.results:
voice_command = result.alternatives[0].transcript
from google.cloud import firestore
from google.cloud.vision import ImageAnnotatorClient
from google.cloud.speech import SpeechClient, RecognitionAudio, RecognitionConfig
from google.cloud import language
from google.cloud.language import enums
from google.cloud.language import types
service_account_name = './service_account.json'
db = firestore.Client.from_service_account_json(service_account_name)
vision_client = ImageAnnotatorClient.from_service_account_json(service_account_name)
speech_client = SpeechClient.from_service_account_json(service_account_name)
language_client = language.LanguageServiceClient.from_service_account_json(service_account_name)
def max_window():
return 60
def database():
return db
def vision():
return vision_client
def speech():
return speech_client, RecognitionAudio, RecognitionConfig
def language(text):
document = types.Document(content = text,
type = enums.Document.Type.PLAIN_TEXT)
return language_client, document
class SpeechToText:
def __init__(self, credential: Union[str, os.PathLike, None] = None):
"""
Args:
credential (str, os.PathLike, None) :
"""
if credential is None:
self.client = SpeechClient()
else:
credentials = Credentials.from_service_account_file(
filename=credential)
self.client = SpeechClient(credentials=credentials)
def recognize_from_uri(
self,
uri: str,
encoding: enums.RecognitionConfig.AudioEncoding = enums.
RecognitionConfig.AudioEncoding.FLAC,
language_code: str = 'en-US',
sampling_rate_hertz: int = 44100) -> types.RecognizeResponse:
"""
Args:
uri (str) :
encoding (enums.RecognitionConfig.AudioEncoding) :
language_code (str) :
sampling_rate_hertz (int) :
Returns:
types.RecognizeResponse
"""
config = types.RecognitionConfig(
encoding=encoding,
language_code=language_code,
sampling_rate_hertz=sampling_rate_hertz)
audio = types.RecognitionAudio(uri=uri)
return self.client.recognize(config, audio)
def recognize_from_file(
self,
file: Union[str, os.PathLike],
encoding: enums.RecognitionConfig.AudioEncoding = enums.
RecognitionConfig.AudioEncoding.FLAC,
language_code: str = 'en-US',
sampling_rate_hertz: int = 44100) -> types.RecognizeResponse:
"""
Args:
file (str, os.PathLike) :
encoding (enums.RecognitionConfig.AudioEncoding) :
language_code (str) :
sampling_rate_hertz (int) :
Returns:
types.RecognizeResponse
"""
config = types.RecognitionConfig(
encoding=encoding,
language_code=language_code,
sampling_rate_hertz=sampling_rate_hertz)
with io.open(file, 'rb') as audio:
content = audio.read()
audio = types.RecognitionAudio(content=content)
return self.client.recognize(config, audio)
def __init__(self):
self.client = SpeechClient()
storage_client = storage.Client()
self.bucket_name = 'cross-culture-audios'
self.bucket = storage_client.get_bucket(self.bucket_name)
class GoogleAsr(Asr):
NAME = 'Google Asr'
DEPENDENCIES = {
'system': [],
'pip' : {
'google-cloud-speech==1.3.1'
}
}
def __init__(self):
super().__init__()
self._credentialsFile = Path(self.Commons.rootDir(), 'credentials/googlecredentials.json')
self._capableOfArbitraryCapture = True
self._isOnlineASR = True
self._client: Optional[SpeechClient] = None
self._streamingConfig: Optional[types.StreamingRecognitionConfig] = None
if self._credentialsFile.exists() and not self.ConfigManager.getAliceConfigByName('googleASRCredentials'):
self.ConfigManager.updateAliceConfiguration(key='googleASRCredentials', value=self._credentialsFile.read_text(), doPreAndPostProcessing=False)
self._internetLostFlag = Event() # Set if internet goes down, cut the decoding
self._lastResultCheck = 0 # The time the intermediate results were last checked. If actual time is greater than this value + 3, stop processing, internet issues
self._previousCapture = '' # The text that was last captured in the iteration
def onStart(self):
super().onStart()
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = str(self._credentialsFile)
self._client = SpeechClient()
# noinspection PyUnresolvedReferences
config = types.RecognitionConfig(
encoding=enums.RecognitionConfig.AudioEncoding.LINEAR16,
sample_rate_hertz=self.AudioServer.SAMPLERATE,
language_code=self.LanguageManager.getLanguageAndCountryCode()
)
self._streamingConfig = types.StreamingRecognitionConfig(config=config, interim_results=True)
def decodeStream(self, session: DialogSession) -> Optional[ASRResult]:
super().decodeStream(session)
recorder = Recorder(self._timeout, session.user, session.deviceUid)
self.ASRManager.addRecorder(session.deviceUid, recorder)
self._recorder = recorder
result = None
with Stopwatch() as processingTime:
with recorder as stream:
audioStream = stream.audioStream()
# noinspection PyUnresolvedReferences
try:
requests = (types.StreamingRecognizeRequest(audio_content=content) for content in audioStream)
responses = self._client.streaming_recognize(self._streamingConfig, requests)
result = self._checkResponses(session, responses)
except Exception as e:
self._internetLostFlag.clear()
self.logWarning(f'Failed ASR request: {e}')
self.end()
return ASRResult(
text=result[0],
session=session,
likelihood=result[1],
processingTime=processingTime.time
) if result else None
def onInternetLost(self):
self._internetLostFlag.set()
def _checkResponses(self, session: DialogSession, responses: Generator) -> Optional[tuple]:
if responses is None:
return None
for response in responses:
if self._internetLostFlag.is_set():
self.logDebug('Internet connectivity lost during ASR decoding')
if not response.results:
raise Exception('Internet connectivity lost during decoding')
result = response.results[0]
return result.alternatives[0].transcript, result.alternatives[0].confidence
if not response.results:
continue
result = response.results[0]
if not result.alternatives:
continue
if result.is_final:
return result.alternatives[0].transcript, result.alternatives[0].confidence
elif result.alternatives[0].transcript != self._previousCapture:
self.partialTextCaptured(session=session, text=result.alternatives[0].transcript, likelihood=result.alternatives[0].confidence, seconds=0)
self._previousCapture = result.alternatives[0].transcript
elif result.alternatives[0].transcript == self._previousCapture:
now = int(time())
if self._lastResultCheck == 0:
self._lastResultCheck = 0
continue
if now > self._lastResultCheck + 3:
self.logDebug(f'Stopping process as there seems to be connectivity issues')
return result.alternatives[0].transcript, result.alternatives[0].confidence
self._lastResultCheck = now
return None
help="connect to unity",
default=False)
parser.add_argument("--lang_code",
type=str,
help="the language code of your language",
default="zh-tw")
args = parser.parse_args()
if args.connect:
address = ('127.0.0.1', 5067)
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.connect(address)
else:
sock = None
client = SpeechClient()
config = types.RecognitionConfig(
encoding=enums.RecognitionConfig.AudioEncoding.LINEAR16,
sample_rate_hertz=RATE,
language_code=args.lang_code)
streaming_config = types.StreamingRecognitionConfig(config=config,
interim_results=True)
print("%s recognition started!" % args.lang_code)
while True:
with MicrophoneStream(RATE, CHUNK) as stream:
audio_generator = stream.generator()
requests = (types.StreamingRecognizeRequest(audio_content=content)
for content in audio_generator)
try:
responses = client.streaming_recognize(streaming_config,
class GoogleAsr(Asr):
NAME = 'Google Asr'
DEPENDENCIES = {'system': [], 'pip': {'google-cloud-speech==1.3.1'}}
def __init__(self):
super().__init__()
self._capableOfArbitraryCapture = True
self._isOnlineASR = True
self._client: Optional[SpeechClient] = None
self._streamingConfig: Optional[
types.StreamingRecognitionConfig] = None
self._previousCapture = ''
def onStart(self):
super().onStart()
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = str(
Path(self.Commons.rootDir(), 'credentials/googlecredentials.json'))
self._client = SpeechClient()
# noinspection PyUnresolvedReferences
config = types.RecognitionConfig(
encoding=enums.RecognitionConfig.AudioEncoding.LINEAR16,
sample_rate_hertz=self.AudioServer.SAMPLERATE,
language_code=self.LanguageManager.getLanguageAndCountryCode())
self._streamingConfig = types.StreamingRecognitionConfig(
config=config, interim_results=True)
def decodeStream(self, session: DialogSession) -> Optional[ASRResult]:
super().decodeStream(session)
recorder = Recorder(self._timeout, session.user, session.siteId)
self.ASRManager.addRecorder(session.siteId, recorder)
self._recorder = recorder
with Stopwatch() as processingTime:
with recorder as stream:
audioStream = stream.audioStream()
# noinspection PyUnresolvedReferences
try:
requests = (types.StreamingRecognizeRequest(
audio_content=content) for content in audioStream)
responses = self._client.streaming_recognize(
self._streamingConfig, requests)
result = self._checkResponses(session, responses)
except:
self.logWarning('Failed ASR request')
self.end()
return ASRResult(
text=result[0],
session=session,
likelihood=result[1],
processingTime=processingTime.time) if result else None
def _checkResponses(self, session: DialogSession,
responses: Generator) -> Optional[tuple]:
if responses is None:
return None
for response in responses:
if not response.results:
continue
result = response.results[0]
if not result.alternatives:
continue
if result.is_final:
return result.alternatives[0].transcript, result.alternatives[
0].confidence
elif result.alternatives[0].transcript != self._previousCapture:
self.partialTextCaptured(
session=session,
text=result.alternatives[0].transcript,
likelihood=result.alternatives[0].confidence,
seconds=0)
self._previousCapture = result.alternatives[0].transcript
return None
class GoogleAsr(Asr):
NAME = 'Google Asr'
DEPENDENCIES = {'system': [], 'pip': {'google-cloud-speech==1.3.1'}}
def __init__(self):
super().__init__()
self._capableOfArbitraryCapture = True
self._isOnlineASR = True
self._client: Optional[SpeechClient] = None
self._streamingConfig: Optional[
types.StreamingRecognitionConfig] = None
self._internetLostFlag = Event(
) # Set if internet goes down, cut the decoding
self._lastResultCheck = 0 # The time the intermediate results were last checked. If actual time is greater than this value + 3, stop processing, internet issues
self._previousCapture = '' # The text that was last captured in the iteration
self._delayedGoogleConfirmation = False # set whether slow internet is detected or not
def onStart(self):
super().onStart()
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = str(
Path(self.Commons.rootDir(), 'credentials/googlecredentials.json'))
self._client = SpeechClient()
# noinspection PyUnresolvedReferences
config = types.RecognitionConfig(
encoding=enums.RecognitionConfig.AudioEncoding.LINEAR16,
sample_rate_hertz=self.AudioServer.SAMPLERATE,
language_code=self.LanguageManager.getLanguageAndCountryCode())
self._streamingConfig = types.StreamingRecognitionConfig(
config=config, interim_results=True)
def decodeStream(self, session: DialogSession) -> Optional[ASRResult]:
super().decodeStream(session)
recorder = Recorder(self._timeout, session.user, session.siteId)
self.ASRManager.addRecorder(session.siteId, recorder)
self._recorder = recorder
result = None
with Stopwatch() as processingTime:
with recorder as stream:
audioStream = stream.audioStream()
# noinspection PyUnresolvedReferences
try:
requests = (types.StreamingRecognizeRequest(
audio_content=content) for content in audioStream)
responses = self._client.streaming_recognize(
self._streamingConfig, requests)
result = self._checkResponses(session, responses)
except:
self._internetLostFlag.clear()
self.logWarning('Failed ASR request')
self.end()
return ASRResult(
text=result[0],
session=session,
likelihood=result[1],
processingTime=processingTime.time) if result else None
def onInternetLost(self):
self._internetLostFlag.set()
def _checkResponses(self, session: DialogSession,
responses: Generator) -> Optional[tuple]:
if responses is None:
return None
for response in responses:
if self._internetLostFlag.is_set():
self.logDebug('Internet connectivity lost during ASR decoding')
if not response.results:
raise Exception(
'Internet connectivity lost during decoding')
result = response.results[0]
return result.alternatives[0].transcript, result.alternatives[
0].confidence
if not response.results:
continue
result = response.results[0]
if not result.alternatives:
continue
if result.is_final:
self._lastResultCheck = 0
self._delayedGoogleConfirmation = False
# print(f'Text confirmed by Google')
return result.alternatives[0].transcript, result.alternatives[
0].confidence
elif result.alternatives[0].transcript != self._previousCapture:
self.partialTextCaptured(
session=session,
text=result.alternatives[0].transcript,
likelihood=result.alternatives[0].confidence,
seconds=0)
# below function captures the "potential" full utterance not just one word from it
if len(self._previousCapture) <= len(
result.alternatives[0].transcript):
self._previousCapture = result.alternatives[0].transcript
elif result.alternatives[0].transcript == self._previousCapture:
# If we are here it's cause google hasn't responded yet with confirmation on captured text
# Store the time in seconds since epoch
now = int(time())
# Set a reference to nows time plus 3 seconds
self._lastResultCheck = now + 3
# wait 3 seconds and see if google responds
if not self._delayedGoogleConfirmation:
# print(f'Text of "{self._previousCapture}" captured but not confirmed by GoogleASR yet')
while now <= self._lastResultCheck:
now = int(time())
self._delayedGoogleConfirmation = True
# Give google the option to still process the utterance
continue
# During next iteration, If google hasn't responded in 3 seconds assume intent is correct
if self._delayedGoogleConfirmation:
self.logDebug(
f'Stopping process as there seems to be connectivity issues'
)
self._lastResultCheck = 0
self._delayedGoogleConfirmation = False
return result.alternatives[
0].transcript, result.alternatives[0].confidence
return None
