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Overview

The text-to-speech endpoint in Livepeer utilizes Parler-TTS, specifically parler-tts/parler-tts-large-v1. This model can generate speech with customizable characteristics such as voice type, speaking style, and audio quality.

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Basic Usage Instructions

For a detailed understanding of the text-to-speech endpoint and to experiment with the API, see the Livepeer AI API Reference.
To use the text-to-speech feature, submit a POST request to the /text-to-speech endpoint. Here’s an example of how to structure your request: 
curl -X POST "http://<GATEWAY_IP>/text-to-speech" \
    -H "Content-Type: application/json" \
    -d '{
        "model_id": "parler-tts/parler-tts-large-v1",
        "text": "A cool cat on the beach",
        "description": "Jon his voice is monotone yet slightly fast in delivery, with a very close recording that almost has no background noise."
    }'

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Request Parameters

  • model_id: The ID of the text-to-speech model to use. Currently, this should be set to "parler-tts/parler-tts-large-v1".
  • text: The text you want to convert to speech.
  • description: A description of the desired voice characteristics. This can include details about the speaker’s voice, speaking style, and audio quality.

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Voice Customization

You can customize the generated voice by adjusting the description parameter. Some aspects you can control include:
  • Speaker identity (e.g., “Jon’s voice”)
  • Speaking style (e.g., “monotone”, “expressive”)
  • Speaking speed (e.g., “slightly fast”)
  • Audio quality (e.g., “very close recording”, “no background noise”)
The checkpoint was trained on 34 speakers. The full list of available speakers includes: Laura, Gary, Jon, Lea, Karen, Rick, Brenda, David, Eileen, Jordan, Mike, Yann, Joy, James, Eric, Lauren, Rose, Will, Jason, Aaron, Naomie, Alisa, Patrick, Jerry, Tina, Jenna, Bill, Tom, Carol, Barbara, Rebecca, Anna, Bruce, and Emily. However, the models performed better with certain speakers. A list of the top 20 speakers for each model variant, ranked by their average speaker similarity scores can be found here

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Limitations and Considerations

  • The maximum length of the input text may be limited. For long-form content, you will need to split your text into smaller chunks. The training default configuration in parler-tts is max 30sec, max text length 600 characters. https://github.com/huggingface/parler-tts/blob/main/training/README.md#3-training
  • While the model supports various voice characteristics, the exact replication of a specific speaker’s voice is not guaranteed.
  • The quality of the generated speech can vary based on the complexity of the input text and the specificity of the voice description.

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Orchestrator Configuration

To configure your Orchestrator to serve the text-to-speech 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 text-to-speech 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 current recommended pricing for this pipeline is 1.5e-6 USD per character.

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Pipeline-Specific Image

To serve the text-to-speech pipeline, you must use a pipeline specific AI Runner container. Pull the required container from Docker Hub using the following command: 
docker pull livepeer/ai-runner:text-to-speech

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API Reference

API Reference

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