Convertissons la voix en texte à l'aide du SDK Azure Speech.
Connectez-vous au portail Azure et créez un service vocal.
Accédez à la ressource que vous avez créée et faites une copie de la clé et de l'emplacement.
conda create -n py36 python=3.6
conda activate py36
Quatre. Installez la bibliothèque.
pip install azure-cognitiveservices-speech
Cinq. Créez un programme.
C'est un programme qui affiche le résultat de la reconnaissance en entrant la voix une seule fois. Collez la clé que vous avez copiée précédemment dans «YourSubscriptionKey» et l'emplacement que vous avez copié précédemment dans «YourServiceRegion». Je veux reconnaître le japonais, alors réglez la langue sur "ja-JP".
import azure.cognitiveservices.speech as speechsdk
Creates an instance of a speech config with specified subscription key and service region.
Replace with your own subscription key and service region (e.g., "westus").
speech_key, service_region, language = "YourSubscriptionKey", "YourServiceRegion", "ja-JP"
speech_config = speechsdk.SpeechConfig(subscription=speech_key, region=service_region)
Creates a recognizer with the given settings
speech_recognizer = speechsdk.SpeechRecognizer(speech_config=speech_config)
print("Say something...")
Starts speech recognition, and returns after a single utterance is recognized. The end of a
single utterance is determined by listening for silence at the end or until a maximum of 15
seconds of audio is processed. The task returns the recognition text as result.
Note: Since recognize_once() returns only a single utterance, it is suitable only for single
shot recognition like command or query.
For long-running multi-utterance recognition, use start_continuous_recognition() instead.
result = speech_recognizer.recognize_once()
Checks result.
if result.reason == speechsdk.ResultReason.RecognizedSpeech:
print("Recognized: {}".format(result.text))
elif result.reason == speechsdk.ResultReason.NoMatch:
print("No speech could be recognized: {}".format(result.no_match_details))
elif result.reason == speechsdk.ResultReason.Canceled:
cancellation_details = result.cancellation_details
print("Speech Recognition canceled: {}".format(cancellation_details.reason))
if cancellation_details.reason == speechsdk.CancellationReason.Error:
print("Error details: {}".format(cancellation_details.error_details))
Il s'agit d'un programme qui saisit en permanence la voix et affiche le résultat de la reconnaissance. De même, veuillez définir la clé, l'emplacement et la langue.
import azure.cognitiveservices.speech as speechsdk
import time
Creates an instance of a speech config with specified subscription key and service region.
Replace with your own subscription key and service region (e.g., "westus").
speech_key, service_region, language = "YourSubscriptionKey", "YourServiceRegion", "ja-JP"
speech_config = speechsdk.SpeechConfig(
subscription=speech_key, region=service_region, speech_recognition_language=language)
Creates a recognizer with the given settings
speech_recognizer = speechsdk.SpeechRecognizer(speech_config=speech_config)
print("Say something...")
def recognized(evt):
print('「{}」'.format(evt.result.text))
# do something
def start(evt):
print('SESSION STARTED: {}'.format(evt))
def stop(evt):
print('SESSION STOPPED {}'.format(evt))
speech_recognizer.recognized.connect(recognized)
speech_recognizer.session_started.connect(start)
speech_recognizer.session_stopped.connect(stop)
try:
speech_recognizer.start_continuous_recognition()
time.sleep(60)
except KeyboardInterrupt:
print("bye.")
speech_recognizer.recognized.disconnect_all()
speech_recognizer.session_started.disconnect_all()
speech_recognizer.session_stopped.disconnect_all()
python stt.py
Le résultat de la reconnaissance s'affiche comme suit.
La méthode d'installation est la même que ci-dessus.
Créez un programme.
Un programme qui lit les fichiers .wav et affiche les résultats de la reconnaissance vocale. Définissez la clé et l'emplacement.
import azure.cognitiveservices.speech as speechsdk
Creates an instance of a speech config with specified subscription key and service region.
Replace with your own subscription key and region identifier from here: https://aka.ms/speech/sdkregion
speech_key, service_region = "YourSubscriptionKey", "YourServiceRegion"
speech_config = speechsdk.SpeechConfig(subscription=speech_key, region=service_region)
Creates an audio configuration that points to an audio file.
Replace with your own audio filename.
audio_filename = "aboutSpeechSdk.wav"
audio_input = speechsdk.audio.AudioConfig(filename=audio_filename)
Creates a recognizer with the given settings
speech_recognizer = speechsdk.SpeechRecognizer(speech_config=speech_config, audio_config=audio_input)
print("Recognizing first result...")
Starts speech recognition, and returns after a single utterance is recognized. The end of a
single utterance is determined by listening for silence at the end or until a maximum of 15
seconds of audio is processed. The task returns the recognition text as result.
Note: Since recognize_once() returns only a single utterance, it is suitable only for single
shot recognition like command or query.
For long-running multi-utterance recognition, use start_continuous_recognition() instead.
result = speech_recognizer.recognize_once()
Checks result.
if result.reason == speechsdk.ResultReason.RecognizedSpeech:
print("Recognized: {}".format(result.text))
elif result.reason == speechsdk.ResultReason.NoMatch:
print("No speech could be recognized: {}".format(result.no_match_details))
elif result.reason == speechsdk.ResultReason.Canceled:
cancellation_details = result.cancellation_details
print("Speech Recognition canceled: {}".format(cancellation_details.reason))
if cancellation_details.reason == speechsdk.CancellationReason.Error:
print("Error details: {}".format(cancellation_details.error_details))
Pour les fichiers audio, utilisez sampledata \ audiofiles \ aboutSpeechSdk.wav dans cognitif-services-speech-sdk.
python stt_from_file.py
Si la clé et l'emplacement sont incorrects, vous obtiendrez l'erreur suivante.
(py36) C:\Users\good_\Documents\PythonProjects\AzureSpeech>python stt_from_file.py
Recognizing first result...
Speech Recognition canceled: CancellationReason.Error
Error details: Connection failed (no connection to the remote host). Internal error: 1. Error details: 11001. Please check network connection, firewall setting, and the region name used to create speech factory. SessionId: 77ad7686a9d94b7882398ae8b855d903
Le résultat est le suivant.
Il a 52 secondes, mais il semble se terminer lorsqu'il reconnaît la première ligne.
Quatre. Pour lire en continu et reconnaître la voix, procédez comme suit.
import azure.cognitiveservices.speech as speechsdk
import time
Creates an instance of a speech config with specified subscription key and service region.
Replace with your own subscription key and region identifier from here: https://aka.ms/speech/sdkregion
speech_key, service_region = "YourSubscriptionKey", "YourServiceRegion"
speech_config = speechsdk.SpeechConfig(subscription=speech_key, region=service_region)
Creates an audio configuration that points to an audio file.
Replace with your own audio filename.
audio_filename = "aboutSpeechSdk.wav"
audio_input = speechsdk.audio.AudioConfig(filename=audio_filename)
Creates a recognizer with the given settings
speech_recognizer = speechsdk.SpeechRecognizer(speech_config=speech_config, audio_config=audio_input)
print("Recognizing...")
def recognized(evt):
print('「{}」'.format(evt.result.text))
# do something
def start(evt):
print('SESSION STARTED: {}'.format(evt))
def stop(evt):
print('SESSION STOPPED {}'.format(evt))
speech_recognizer.recognized.connect(recognized)
speech_recognizer.session_started.connect(start)
speech_recognizer.session_stopped.connect(stop)
try:
speech_recognizer.start_continuous_recognition()
time.sleep(60)
except KeyboardInterrupt:
print("bye.")
speech_recognizer.recognized.disconnect_all()
speech_recognizer.session_started.disconnect_all()
speech_recognizer.session_stopped.disconnect_all()
Cinq. Essayons encore.
Il semble que la reconnaissance vocale soit possible en continu comme indiqué ci-dessous!
Je vous remercie pour votre travail acharné.
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