SpeechToTextLoader#

class langchain_google_community.google_speech_to_text.SpeechToTextLoader(project_id: str, file_path: str, location: str = 'us-central1', recognizer_id: str = '_', config: RecognitionConfig | None = None, config_mask: FieldMask | None = None, is_long: bool = False)[source]#

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
is_long (bool) – use async Cloud Speech recognition, mainly for long documents For more information: https://cloud.google.com/speech-to-text/v2/docs/batch-recognize

Methods

`__init__`(project_id, file_path[, location, ...])	Initializes the GoogleSpeechToTextLoader.
`alazy_load`()	A lazy loader for Documents.
`aload`()	Load data into Document objects.
`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: RecognitionConfig | None = None, config_mask: FieldMask | None = None, is_long: bool = False)[source]#

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
is_long (bool) – use async Cloud Speech recognition, mainly for long documents For more information: https://cloud.google.com/speech-to-text/v2/docs/batch-recognize

async alazy_load() → AsyncIterator[Document]#

A lazy loader for Documents.

Return type:: AsyncIterator[Document]

async aload() → list[Document]#

Load data into Document objects.

Return type:: list[Document]

lazy_load() → Iterator[Document]#

A lazy loader for Documents.

Return type:: Iterator[Document]

load() → List[Document][source]#

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: TextSplitter | None = 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]