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Overview

The audio-to-text pipeline converts audio from media files into text, utilizing cutting-edge diffusion models from HuggingFace’s automatic-speech-recognition (ASR) pipeline.

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Models

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Warm Models

The current warm model requested for the audio-to-text pipeline is:
  • openai/whisper-large-v3: Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation.
For faster responses with different audio-to-text diffusion models, ask Orchestrators to load it on their GPU via the ai-video channel in Discord Server.

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On-Demand Models

The following models have been tested and verified for the audio-to-text pipeline:
If a specific model you wish to use is not listed, please submit a feature request on GitHub to get the model verified and added to the list.

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Basic Usage Instructions

For a detailed understanding of the audio-to-text endpoint and to experiment with the API, see the Livepeer AI API Reference.
To create an audio transcript using the audio-to-text pipeline, submit a POST request to the Gateway’s audio-to-text API endpoint: 
curl -X POST "https://<GATEWAY_IP>/audio-to-text" \
    -F model_id=openai/whisper-large-v3 \
    -F audio=@<PATH_TO_FILE>
In this command:
  • <GATEWAY_IP> should be replaced with your AI Gateway’s IP address.
  • model_id is the diffusion model for audio transcription.
  • audio is the path to the audio file to be transcribed.
  • Supported file types: mp4, webm, mp3, flac, wav and m4a - Maximum request size: 50 MB
For additional optional parameters, refer to the Livepeer AI API Reference. After execution, the Orchestrator processes the request and returns the response to the Gateway: 
{
  "chunks": [
    {
      "text": " Explore the power of automatic speech recognition",
      "timestamp": [0, 1.35]
    },
    {
      "text": " By extracting the text from audio",
      "timestamp": [1.35, 2.07]
    }
  ],
  "text": " Explore the power of automatic speech recognition By extracting the text from audio"
}

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Orchestrator Configuration

To configure your Orchestrator to serve the audio-to-text pipeline, refer to the Orchestrator Configuration guide.

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System Requirements

The following system requirements are recommended for optimal performance:
We are planning to simplify the pricing in the future so orchestrators can set one AI price per compute unit and have the system automatically scale based on the model’s compute requirements.
The pricing for the audio-to-text pipeline is based on competitor pricing. However, we strongly encourage orchestrators to set their own pricing based on their costs and requirements. Setting a competitive price will help attract more jobs, as Gateways can set their maximum price for a job. The currently recommended pricing for this pipeline is 0.02e-6 USD per milliseconds of audio input.

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API Reference

API Reference

Explore the audio-to-text endpoint and experiment with the API in the Livepeer AI API Reference.