Transcription

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)

__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

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 isinstance(audio, (str, tuple, np.ndarray)) 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 isinstance(audio, (str, tuple, np.ndarray)) else results