txtai - Transcription (original) (raw)
The Transcription pipeline converts speech in audio files to text.
Example
The following shows a simple example using this pipeline.
`from txtai.pipeline import Transcription
Create and run pipeline
transcribe = Transcription() transcribe("path to wav file") `
This pipeline may require additional system dependencies. See this section for more.
See the links below for a more detailed example.
| Notebook | Description | |
|---|---|---|
| Transcribe audio to text | Convert audio files to text |  |
| Speech to Speech RAG ▶️ | Full cycle speech to speech workflow with RAG | |
Configuration-driven example
Pipelines are run with Python or configuration. Pipelines can be instantiated in configuration using the lower case name of the pipeline. Configuration-driven pipelines are run with workflows or the API.
config.yml
`# Create pipeline using lower case class name transcription:
Run pipeline with workflow
workflow: transcribe: tasks: - action: transcription `
Run with Workflows
`from txtai import Application
Create and run pipeline with workflow
app = Application("config.yml") list(app.workflow("transcribe", ["path to wav file"])) `
Run with API
`CONFIG=config.yml uvicorn "txtai.api:app" &
curl
-X POST "http://localhost:8000/workflow"
-H "Content-Type: application/json"
-d '{"name":"transcribe", "elements":["path to wav file"]}'
`
Methods
Python documentation for the pipeline.
__init__(path=None, quantize=False, gpu=True, model=None, **kwargs)
Source code in txtai/pipeline/audio/transcription.py
| def __init__(self, path=None, quantize=False, gpu=True, model=None, **kwargs): if not TRANSCRIPTION: raise ImportError( 'Transcription pipeline is not available - install "pipeline" extra to enable. Also check that libsndfile is available.' ) # Call parent constructor super().__init__("automatic-speech-recognition", path, quantize, gpu, model, **kwargs) |
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__call__(audio, rate=None, chunk=10, join=True, **kwargs)
Transcribes audio files or data to text.
This method supports a single audio element or a list of audio. If the input is audio, the return type is a string. If text is a list, a list of strings is returned
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
| audio | audio|list | required | |
| rate | sample rate, only required with raw audio data | None | |
| chunk | process audio in chunk second sized segments | 10 | |
| join | if True (default), combine each chunk back together into a single text output. When False, chunks are returned as a list of dicts, each having raw associated audio and sample rate in addition to text | True | |
| kwargs | generate keyword arguments | {} |
Returns:
| Type | Description |
|---|---|
| list of transcribed text |
Source code in txtai/pipeline/audio/transcription.py
| 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 | def __call__(self, audio, rate=None, chunk=10, join=True, **kwargs): """ Transcribes audio files or data to text. This method supports a single audio element or a list of audio. If the input is audio, the return type is a string. If text is a list, a list of strings is returned Args: audio: audio|list rate: sample rate, only required with raw audio data chunk: process audio in chunk second sized segments join: if True (default), combine each chunk back together into a single text output. When False, chunks are returned as a list of dicts, each having raw associated audio and sample rate in addition to text kwargs: generate keyword arguments Returns: list of transcribed text """ # Convert single element to list values = [audio] if self.isaudio(audio) else audio # Read input audio speech = self.read(values, rate) # Apply transformation rules and store results results = self.batchprocess(speech, chunk, **kwargs) if chunk and not join else self.process(speech, chunk, **kwargs) # Return single element if single element passed in return results[0] if self.isaudio(audio) else results |
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