langchain_community.document_loaders.google_speech_to_text.GoogleSpeechToTextLoader

class langchain_community.document_loaders.google_speech_to_text.GoogleSpeechToTextLoader(project_id: str, file_path: str, location: str = 'us-central1', recognizer_id: str = '_', config: Optional[RecognitionConfig] = None, config_mask: Optional[FieldMask] = None)

Loader for Google Cloud Speech-to-Text audio transcripts.

It uses the Google Cloud Speech-to-Text API to transcribe audio files and loads the transcribed text into one or more Documents, depending on the specified format.

To use, you should have the google-cloud-speech python package installed.

Audio files can be specified via a Google Cloud Storage uri or a local file path.

For a detailed explanation of Google Cloud Speech-to-Text, refer to the product documentation. https://cloud.google.com/speech-to-text

Initializes the GoogleSpeechToTextLoader.

Parameters

• project_id (str) – Google Cloud Project ID.

• file_path (str) – A Google Cloud Storage URI or a local file path.

• location (str) – Speech-to-Text recognizer location.

• recognizer_id (str) – Speech-to-Text recognizer id.

• config (Optional[RecognitionConfig]) – Recognition options and features. For more information: https://cloud.google.com/python/docs/reference/speech/latest/google.cloud.speech_v2.types.RecognitionConfig

• config_mask (Optional[FieldMask]) – The list of fields in config that override the values in the default_recognition_config of the recognizer during this recognition request. For more information: https://cloud.google.com/python/docs/reference/speech/latest/google.cloud.speech_v2.types.RecognizeRequest

Methods

__init__(project_id, file_path[, location, ...])	Initializes the GoogleSpeechToTextLoader.
alazy_load()	A lazy loader for Documents.
lazy_load()	A lazy loader for Documents.
load()	Transcribes the audio file and loads the transcript into documents.
load_and_split([text_splitter])	Load Documents and split into chunks.

__init__(project_id: str, file_path: str, location: str = 'us-central1', recognizer_id: str = '_', config: Optional[RecognitionConfig] = None, config_mask: Optional[FieldMask] = None)

Initializes the GoogleSpeechToTextLoader.

Parameters

• project_id (str) – Google Cloud Project ID.

• file_path (str) – A Google Cloud Storage URI or a local file path.

• location (str) – Speech-to-Text recognizer location.

• recognizer_id (str) – Speech-to-Text recognizer id.

• config (Optional[RecognitionConfig]) – Recognition options and features. For more information: https://cloud.google.com/python/docs/reference/speech/latest/google.cloud.speech_v2.types.RecognitionConfig

• config_mask (Optional[FieldMask]) – The list of fields in config that override the values in the default_recognition_config of the recognizer during this recognition request. For more information: https://cloud.google.com/python/docs/reference/speech/latest/google.cloud.speech_v2.types.RecognizeRequest

async alazy_load() → AsyncIterator[Document]

A lazy loader for Documents.

Return type

AsyncIterator[Document]

lazy_load() → Iterator[Document]

A lazy loader for Documents.

Return type

Iterator[Document]

load() → List[Document]

Transcribes the audio file and loads the transcript into documents.

It uses the Google Cloud Speech-to-Text API to transcribe the audio file and blocks until the transcription is finished.

Return type

List[Document]

load_and_split(text_splitter: Optional[TextSplitter] = None) → List[Document]

Load Documents and split into chunks. Chunks are returned as Documents.

Do not override this method. It should be considered to be deprecated!

Parameters

text_splitter (Optional[TextSplitter]) – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacterTextSplitter.

Returns

List of Documents.

Return type

List[Document]

Examples using GoogleSpeechToTextLoader

• Google Cloud Speech-to-Text