> ## Documentation Index
> Fetch the complete documentation index at: https://docs.livepeer.org/llms.txt
> Use this file to discover all available pages before exploring further.

# Text-to-Speech

## Overview

The text-to-speech endpoint in Livepeer utilizes
[Parler-TTS](https://github.com/huggingface/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.

## Basic Usage Instructions

<Tip>
  For a detailed understanding of the `text-to-speech` endpoint and to
  experiment with the API, see the [Livepeer AI API
  Reference](/ai/api-reference/text-to-speech).
</Tip>

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:

```bash theme={"theme":{"light":"github-light","dark":"dark-plus"}}
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."
    }'
```

### 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.

### 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](https://github.com/huggingface/parler-tts/blob/main/INFERENCE.md#speaker-consistency)

## 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](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.

## Orchestrator Configuration

To configure your Orchestrator to serve the `text-to-speech` pipeline, refer to
the [Orchestrator Configuration](/ai/orchestrators/get-started) guide.

### System Requirements

The following system requirements are recommended for optimal performance:

* [NVIDIA GPU](https://developer.nvidia.com/cuda-gpus) with **at least 12GB** of
  VRAM.

## Recommended Pipeline Pricing

<Note>
  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.
</Note>

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**.

### 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](https://hub.docker.com/r/livepeer/ai-runner/tags?name=text-to-speech-latest)
using the following command:

```bash theme={"theme":{"light":"github-light","dark":"dark-plus"}}
docker pull livepeer/ai-runner:text-to-speech
```

## API Reference

<Card title="API Reference" icon="rectangle-terminal" href="/ai/api-reference/text-to-speech">
  Explore the `text-to-speech` endpoint and experiment with the API in the
  Livepeer AI API Reference.
</Card>