def voice_from_text(text, path):
filepath = "{}/speech_{}.wav".format(path, str(uuid.uuid1().hex))
if os.path.isfile(filepath): os.remove(filepath)
ssml_string = """
<speak version="1.0" xmlns="http://www.w3.org/2001/10/synthesis"
xmlns:mstts="https://www.w3.org/2001/mstts" xml:lang="en-US">
<voice name="en-US-JennyNeural">
<mstts:express-as style="chat">
{}
</mstts:express-as>
</voice>
</speak>
""".format(text)
speech_config = speechsdk.SpeechConfig(
subscription=api_keys["microsoft-speech"]["key"],
region=api_keys["microsoft-speech"]["region"])
# audio_config = AudioOutputConfig(filename=filepath)
synthesizer = SpeechSynthesizer(speech_config=speech_config,
audio_config=None)
result = synthesizer.speak_ssml_async(ssml_string).get()
stream = AudioDataStream(result)
stream.save_to_wav_file(filepath)
synthesizer.speak_text_async(text)
return filepath
def generaraudio():
archivo = open("uploads/archivo.txt", "r")
documentos = archivo.read()
documentos = documentos.rstrip('\n')
synthesizer = SpeechSynthesizer(speech_config=speech_config,
audio_config=audio_config)
synthesizer.speak_text_async(documentos)
def voice_from_text(text, path):
filepath = "{}/speech.wav".format(path)
if os.path.isfile(filepath): os.remove(filepath)
speech_config = speechsdk.SpeechConfig(subscription=api_keys["microsoft-speech"]["key"], region=api_keys["microsoft-speech"]["region"])
audio_config = AudioOutputConfig(filename=filepath)
synthesizer = SpeechSynthesizer(speech_config=speech_config, audio_config=audio_config)
synthesizer.speak_text_async("The Birch canoe slid on the smooth planks. Glue the sheet to the dark blue background.")
return path
def result():
message = request.form['message']
number = request.form['number']
speech_config = SpeechConfig(
subscription="0a6a0817af9f46aea9054beaa3d30290", region="westeurope")
audio_config = AudioOutputConfig(filename="message_fr.wav")
speech_config.speech_synthesis_voice_name = "fr-FR-DeniseNeural"
synthesizer = SpeechSynthesizer(speech_config=speech_config,
audio_config=audio_config)
synthesizer.speak_text_async(message)
# Add your subscription key and endpoint
subscription_key = "e134037165514c648a57bf6ccc95e541"
endpoint = "https://api.cognitive.microsofttranslator.com"
# Add your location, also known as region. The default is global.
# This is required if using a Cognitive Services resource.
location = "francecentral"
path = '/translate'
constructed_url = endpoint + path
params = {'api-version': '3.0', 'from': 'fr', 'to': ['en']}
constructed_url = endpoint + path
headers = {
'Ocp-Apim-Subscription-Key': subscription_key,
'Ocp-Apim-Subscription-Region': location,
'Content-type': 'application/json',
'X-ClientTraceId': str(uuid.uuid4())
}
# You can pass more than one object in body.
body = [{'text': message}]
quest = requests.post(constructed_url,
params=params,
headers=headers,
json=body)
response = quest.json()
translator = response[0]["translations"][0]["text"]
audio_config = AudioOutputConfig(filename="message_en.wav")
speech_config.speech_synthesis_voice_name = "en-US-AriaNeural"
synthesizer = SpeechSynthesizer(speech_config=speech_config,
audio_config=audio_config)
synthesizer.speak_text_async(translator)
data = {"number": number}
with open("limit.json", "w") as file:
json.dump(data, file)
return (message)
def welcome_message(name):
speech_config = speechsdk.SpeechConfig(
subscription="b58d19e457574aa39bc0f8b9b763cd55",
region="australiaeast")
audio_config = AudioOutputConfig(
filename=
"C:/Users/Pranav Patel/Documents/schabu/back_end/python/welcome.wav")
synthesizer = SpeechSynthesizer(speech_config=speech_config,
audio_config=audio_config)
text = "Hello " + name + "! Welcome to Schubu Recrutiment Process. Please Click on the Start button to begin the interview process."
synthesizer.speak_text_async(text)
print(text)
def tts(item):
speech_config = SpeechConfig(
subscription="bc0912f626b44d5a8bb00e4497644fa4", region="westus")
audio_config = AudioOutputConfig(filename="./result.wav")
synthesizer = SpeechSynthesizer(speech_config=speech_config,
audio_config=audio_config)
appendString = ""
# if res == "OK":
# appendString = "is in direction you're looking"
# else:
# appendString = "is not in direction you're looking"
#
result = synthesizer.speak_text_async(item + appendString).get()
stream = AudioDataStream(result)
stream.save_to_wav_file("./result.mp3")
#!/usr/bin/python3
from azure.cognitiveservices.speech import AudioDataStream, SpeechConfig, SpeechSynthesizer, SpeechSynthesisOutputFormat
import azure.cognitiveservices.speech as speechsdk
from azure.cognitiveservices.speech.audio import AudioOutputConfig
voice = "zh-CN-XiaoxiaoNeural"
text = '你好'
speech_config = SpeechConfig(subscription="3cb77646eea84168b348969306ff2a3c",
region="eastus")
speech_config.speech_synthesis_voice_name = voice
audio_config = AudioOutputConfig(filename="file.wav")
synthesizer = SpeechSynthesizer(speech_config=speech_config,
audio_config=audio_config)
result = synthesizer.speak_text_async(text).get()
# Check result
if result.reason == speechsdk.ResultReason.SynthesizingAudioCompleted:
print("Speech synthesized to speaker for text [{}] with voice [{}]".format(
text, voice))
elif result.reason == speechsdk.ResultReason.Canceled:
cancellation_details = result.cancellation_details
print("Speech synthesis canceled: {}".format(cancellation_details.reason))
if cancellation_details.reason == speechsdk.CancellationReason.Error:
print("Error details: {}".format(cancellation_details.error_details))
for img in search_results["value"]][randrange(20)]
print(i2download)
response = requests.get(i2download)
ext = i2download[-3:]
imgfile = open(
"results/{}/{:04d}/{:04d}.{}".format(uuid, snumb, wi, ext), "wb")
imgfile.write(response.content)
imgfile.close()
print("Got {}".format(wi))
time.sleep(2)
audio_config = AudioOutputConfig(
filename="results/{}/{:04d}/wav.wav".format(uuid, snumb))
synthesizer = SpeechSynthesizer(speech_config=speech_config,
audio_config=audio_config)
synthesizer.speak_text_async(sentence)
os.system(
"python collage_maker.py -o results/{0}/slide-{1:04d}.png -f results/{0}/{1:04d} -w 800 -i 600"
.format(uuid, snumb))
print(
'ffmpeg -loop 1 -i results/{0}/slide-{1:04d}.png -i results/{0}/{1:04d}/wav.wav -c:v libx264 -tune stillimage -c:a aac -b:a 192k -pix_fmt yuv420p -shortest results/{0}/{1:04d}.mp4 -vf "pad=ceil(iw/2)*2:ceil(ih/2)*2"'
.format(uuid, snumb))
pngs = [
x for x in os.listdir("results/{}".format(uuid)) if x[-3:] == "png"
]
for png in pngs:
im = Image.open("results/{}/{}".format(uuid, png))
audio_config = AudioOutputConfig(use_default_speaker=True)
synthesizer = SpeechSynthesizer(speech_config=speech_config)
runtimeCredentials = CognitiveServicesCredentials(luis_key)
clientRuntime = LUISRuntimeClient(endpoint=luis_endpoint, credentials=runtimeCredentials)
print("Start listening...")
speech = speech_recognizer.recognize_once()
try:
while speech.text != "Stop":
# Production == slot name
print("Your query is: ", speech.text)
predictionRequest = { "query" : speech.text}
predictionResponse = clientRuntime.prediction.get_slot_prediction(luis_app_id, "Production", predictionRequest)
print("Top intent: {}".format(predictionResponse.prediction.top_intent))
print("Sentiment: {}".format (predictionResponse.prediction.sentiment))
print("Intents: ")
for intent in predictionResponse.prediction.intents:
print("\t{}".format (json.dumps(intent)))
print("Entities: {}".format (predictionResponse.prediction.entities))
synthesizer.speak_text_async("A simple test to write to a file.")
# Use a one-time, synchronous call to transcribe the speech
print("Start listening...")
speech = speech_recognizer.recognize_once()
except Exception as ex:
print(ex)
import azure.cognitiveservices.speech as speechsdk
from azure.cognitiveservices.speech import AudioDataStream, SpeechConfig, SpeechSynthesizer, SpeechSynthesisOutputFormat
from azure.cognitiveservices.speech.audio import AudioOutputConfig
speech_key, service_region = "UseYourSpeechAPI", "eastus"
speech_config = speechsdk.SpeechConfig(subscription=speech_key,
region=service_region)
voice = "Microsoft Server Speech Text to Speech Voice (en-US, GuyNeural)" #en-US-GuyRUS
speech_config.speech_synthesis_voice_name = voice
speech_config.set_speech_synthesis_output_format(
SpeechSynthesisOutputFormat["Riff24Khz16BitMonoPcm"])
audio_config = AudioOutputConfig(filename="c:/OutputVoiceFile.mp3")
synthesizer = SpeechSynthesizer(speech_config=speech_config,
audio_config=audio_config)
synthesizer.speak_text_async(
"Hello World, This is a test of creating a playable mp3 file")
"--audio_name",
required=True,
help="Please Enter Audio File Name(Without extension)")
args = vars(ap.parse_args())
# In[2]:
speech_config = SpeechConfig(subscription="__KEY", region="Region")
# In[3]:
audio_config = AudioOutputConfig(filename="public/python/output_audio_files/" +
args['audio_name'] + "_summary.wav")
# In[4]:
with open("summary/" + args['audio_name'] + "_summary.txt", 'r') as file:
data = file.read().replace('\n', '')
# In[5]:
data
# In[11]:
synthesizer = SpeechSynthesizer(speech_config=speech_config,
audio_config=audio_config)
synthesizer.speak_text_async(data)
# In[ ]:
from azure.cognitiveservices.speech import AudioDataStream, SpeechConfig, SpeechSynthesizer, SpeechSynthesisOutputFormat
from azure.cognitiveservices.speech.audio import AudioOutputConfig
speech_config = SpeechConfig(subscription="546da9a0b95d4b29a806c1c7d8d147bc", region="southcentralus")
audio_config = AudioOutputConfig(filename="file.wav")
archivo = open("archivo.txt", "r")
documents = archivo.read()
documents = documents.rstrip('\n')
synthesizer = SpeechSynthesizer(speech_config=speech_config, audio_config=audio_config)
synthesizer.speak_text_async(documents)
speech_key, service_region = os.getenv('SPEECH_RESOURCE_KEY'), "westus"
# A speech Synthesizer is created with the given settings.
speech_config = SpeechConfig(subscription=speech_key, region=service_region)
print("Enter your choice :")
print("1. Output from speaker")
print("2. Save output to a file\n")
choice = int(input())
# Output is recieved via the device speaker
if (choice == 1):
audio_config = AudioOutputConfig(use_default_speaker=True)
# Output is saved in the files whose name is provided as an input
elif (choice == 2):
audio_config = AudioOutputConfig(
filename=("tts_output/" +
input("Enter the name of the output file : ") + ".wav"))
# A speech Synthesizer is initialized with given settings
synthesizer = SpeechSynthesizer(speech_config=speech_config,
audio_config=audio_config)
# An asynchronous call to the api is made with the input waiting for the output
synthesizer.speak_text_async(input("Enter a string : "))
get_handw_text_results = computervision_client.get_read_result(
operation_id)
if get_handw_text_results.status not in ['notStarted', 'running']:
break
time.sleep(1)
#Crear el archivo de texto donde se guardara el texto obtenido de la imagen
archivo = open("archivo.txt", "w")
# Imprimimos el texto linea por linea
if get_handw_text_results.status == OperationStatusCodes.succeeded:
for text_result in get_handw_text_results.analyze_result.read_results:
for line in text_result.lines:
print(line.text)
archivo.write(line.text)
#print(line.bounding_box)
print()
archivo.close()
###### Código para convertir el texto obtenido y archivado en la imagen en audio ######
#Creacion del audio del texto obtenido
audio_config = AudioOutputConfig(use_default_speaker=True)
# #Escritura del archivo de audio
synthesizer = SpeechSynthesizer(speech_config=speech_config,
audio_config=audio_config)
archivo_string = open("archivo.txt", "r", encoding="utf-8-sig").read()
synthesizer.speak_text_async(archivo_string).get()
#
speech_recognizer = SpeechRecognizer(speech_config=speech_config)
print("Say something...")
result = speech_recognizer.recognize_once()
# Checks result.
if result.reason == ResultReason.RecognizedSpeech:
print("Recognized: {}".format(result.text))
elif result.reason == ResultReason.NoMatch:
print("No speech could be recognized: {}".format(result.no_match_details))
elif result.reason == ResultReason.Canceled:
cancellation_details = cancellation_details
print("Speech Recognition canceled: {}".format(cancellation_details.reason))
if cancellation_details.reason == CancellationReason.Error:
print("Error details: {}".format(cancellation_details.error_details))
#output
audio_config = AudioOutputConfig(use_default_speaker=True)
language_config = SourceLanguageConfig("ko-KR")
synthesizer = SpeechSynthesizer(speech_config=speech_config, audio_config=audio_config)
synthesizer.speak_text_async("result.text")