Transcribe Word Time Offsets
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This sample demonstrates how to transcribe audio with word time offsets using the Speech-to-Text API.
Code sample
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[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],[],[],[],null,["# Transcribe Word Time Offsets\n\nThis sample demonstrates how to transcribe audio with word time offsets using the Speech-to-Text API.\n\nCode sample\n-----------\n\n### Python\n\n\nTo learn how to install and use the client library for Speech-to-Text, see\n[Speech-to-Text client libraries](/speech-to-text/docs/client-libraries).\n\n\nFor more information, see the\n[Speech-to-Text Python API\nreference documentation](/python/docs/reference/speech/latest).\n\n\nTo authenticate to Speech-to-Text, set up Application Default Credentials.\nFor more information, see\n\n[Set up authentication for a local development environment](/docs/authentication/set-up-adc-local-dev-environment).\n\n import os\n\n from google.cloud.speech_v2 import SpeechClient\n from google.cloud.speech_v2.types import cloud_speech\n\n PROJECT_ID = os.getenv(\"GOOGLE_CLOUD_PROJECT\")\n\n\n def transcribe_word_time_offsets_v2(\n audio_file: str,\n ) -\u003e cloud_speech.RecognizeResponse:\n \"\"\"Transcribes an audio file into text using with word time offsets.\n Args:\n audio_file (str): Path to the local audio file to be transcribed.\n Example: \"resources/audio.wav\"\n Returns:\n cloud_speech.RecognizeResponse: The response containing the transcription results\n with word time offsets.\n \"\"\"\n # Instantiates a client\n client = SpeechClient()\n\n # Reads a file as bytes\n with open(audio_file, \"rb\") as file:\n audio_content = file.read()\n\n config = cloud_speech.RecognitionConfig(\n auto_decoding_config=cloud_speech.AutoDetectDecodingConfig(),\n language_codes=[\"en-US\"],\n model=\"long\",\n features=cloud_speech.RecognitionFeatures(\n enable_word_time_offsets=True,\n ),\n )\n\n request = cloud_speech.RecognizeRequest(\n recognizer=f\"projects/{PROJECT_ID}/locations/global/recognizers/_\",\n config=config,\n content=audio_content,\n )\n\n # Transcribes the audio into text\n response = client.recognize(request=request)\n\n for result in response.results:\n print(f\"Transcript: {result.alternatives[0].transcript}\")\n\n return response\n\nWhat's next\n-----------\n\n\nTo search and filter code samples for other Google Cloud products, see the\n[Google Cloud sample browser](/docs/samples?product=speech)."]]