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OpenedAI Speech

An OpenAI API compatible text to speech server.

  • Compatible with the OpenAI audio/speech API
  • Serves the /v1/audio/speech endpoint
  • Not affiliated with OpenAI in any way, does not require an OpenAI API Key
  • A free, private, text-to-speech server with custom voice cloning

Full Compatibility:

  • tts-1: alloy, echo, fable, onyx, nova, and shimmer (configurable)
  • tts-1-hd: alloy, echo, fable, onyx, nova, and shimmer (configurable, uses OpenAI samples by default)
  • response_format: mp3, opus, aac, or flac
  • speed 0.25-4.0 (and more)

Details:

If you find a better voice match for tts-1 or tts-1-hd, please let me know so I can update the defaults.

Recent Changes

Version 0.13.0, 2024-06-25

  • Added Custom fine-tuned XTTS model support
  • Initial prebuilt arm64 image support (Apple M-series, Raspberry Pi - MPS is not supported in XTTS/torch), thanks @JakeStevenson, @hchasens
  • Initial attempt at AMD GPU (ROCm 5.7) support
  • Parler-tts support removed
  • Move the *.default.yaml to the root folder
  • Run the docker as a service by default (restart: unless-stopped)
  • Added audio_reader.py for streaming text input and reading long texts

Version 0.12.3, 2024-06-17

  • Additional logging details for BadRequests (400)

Version 0.12.2, 2024-06-16

  • Fix :min image requirements (numpy<2?)

Version 0.12.0, 2024-06-16

  • Improved error handling and logging
  • Restore the original alloy tts-1-hd voice by default, use alloy-alt for the old voice.

Version 0.11.0, 2024-05-29

  • 🌐 Multilingual support (16 languages) with XTTS
  • Remove high Unicode filtering from the default config/pre_process_map.yaml
  • Update Docker build & app startup. thanks @justinh-rahb
  • Fix: "Plan failed with a cudnnException"
  • Remove piper cuda support

Version: 0.10.1, 2024-05-05

  • Remove runtime: nvidia from docker-compose.yml, this assumes nvidia/cuda compatible runtime is available by default. thanks @jmtatsch

Version: 0.10.0, 2024-04-27

  • Pre-built & tested docker images, smaller docker images (8GB or 860MB)
  • Better upgrades: reorganize config files under config/, voice models under voices/
  • Compatibility! If you customized your voice_to_speaker.yaml or pre_process_map.yaml you need to move them to the config/ folder.
  • default listen host to 0.0.0.0

Version: 0.9.0, 2024-04-23

  • Fix bug with yaml and loading UTF-8
  • New sample text-to-speech application say.py
  • Smaller docker base image
  • Add beta parler-tts support (you can describe very basic features of the speaker voice), See: (https://www.text-description-to-speech.com/) for some examples of how to describe voices. Voices can be defined in the voice_to_speaker.default.yaml. Two example parler-tts voices are included in the voice_to_speaker.default.yaml file. parler-tts is experimental software and is kind of slow. The exact voice will be slightly different each generation but should be similar to the basic description.

...

Version: 0.7.3, 2024-03-20

  • Allow different xtts versions per voice in voice_to_speaker.yaml, ex. xtts_v2.0.2
  • Quality: Fix xtts sample rate (24000 vs. 22050 for piper) and pops

Installation instructions

Create a speech.env environment file

Copy the sample.env to speech.env (customize if needed)

cp sample.env speech.env

Defaults

TTS_HOME=voices
HF_HOME=voices
#PRELOAD_MODEL=xtts
#PRELOAD_MODEL=xtts_v2.0.2
#EXTRA_ARGS=--log-level DEBUG
#USE_ROCM=1

Option A: Manual installation

# install curl and ffmpeg
sudo apt install curl ffmpeg
# Create & activate a new virtual environment (optional but recommended)
python -m venv .venv
source .venv/bin/activate
# Install the Python requirements
# - use requirements-rocm.txt for AMD GPU (ROCm support)
# - use requirements-min.txt for piper only (CPU only)
pip install -r requirements.txt
# run the server
bash startup.sh

On first run, the voice models will be downloaded automatically. This might take a while depending on your network connection.

Option B: Docker Image (recommended)

Nvidia GPU (cuda)

docker compose up

AMD GPU (ROCm support)

docker compose -d docker-compose.rocm.yml up

ARM64 (Apple M-series, Raspberry Pi)

XTTS only has CPU support here and will be very slow, you can use the Nvidia image for XTTS with CPU (slow), or use the piper only image (recommended)

CPU only, No GPU (piper only)

For a minimal docker image with only piper support (<1GB vs. 8GB).

docker compose -f docker-compose.min.yml up

Sample Usage

You can use it like this:

curl http://localhost:8000/v1/audio/speech -H "Content-Type: application/json" -d '{
    "model": "tts-1",
    "input": "The quick brown fox jumped over the lazy dog.",
    "voice": "alloy",
    "response_format": "mp3",
    "speed": 1.0
  }' > speech.mp3

Or just like this:

curl -s http://localhost:8000/v1/audio/speech -H "Content-Type: application/json" -d '{
    "input": "The quick brown fox jumped over the lazy dog."}' > speech.mp3

Or like this example from the OpenAI Text to speech guide:

import openai

client = openai.OpenAI(
  # This part is not needed if you set these environment variables before import openai
  # export OPENAI_API_KEY=sk-11111111111
  # export OPENAI_BASE_URL=http://localhost:8000/v1
  api_key = "sk-111111111",
  base_url = "http://localhost:8000/v1",
)

with client.audio.speech.with_streaming_response.create(
  model="tts-1",
  voice="alloy",
  input="Today is a wonderful day to build something people love!"
) as response:
  response.stream_to_file("speech.mp3")

Also see the say.py sample application for an example of how to use the openai-python API.

# play the audio, requires 'pip install playsound'
python say.py -t "The quick brown fox jumped over the lazy dog." -p
# save to a file in flac format
python say.py -t "The quick brown fox jumped over the lazy dog." -m tts-1-hd -v onyx -f flac -o fox.flac

You can also try the included audio_reader.py for listening to longer text and streamed input.

Example usage:

python audio_reader.py -s 2 < LICENSE # read the software license - fast

OpenAI API Documentation and Guide

Custom Voices Howto

Piper

  1. Select the piper voice and model from the piper samples
  2. Update the config/voice_to_speaker.yaml with a new section for the voice, for example:
...
tts-1:
  ryan:
    model: voices/en_US-ryan-high.onnx
    speaker: # default speaker
  1. New models will be downloaded as needed, of you can download them in advance with download_voices_tts-1.sh. For example:
bash download_voices_tts-1.sh en_US-ryan-high

Coqui XTTS v2

Coqui XTTS v2 voice cloning can work with as little as 6 seconds of clear audio. To create a custom voice clone, you must prepare a WAV file sample of the voice.

Guidelines for preparing good sample files for Coqui XTTS v2

  • Mono (single channel) 22050 Hz WAV file
  • 6-30 seconds long - longer isn't always better (I've had some good results with as little as 4 seconds)
  • low noise (no hiss or hum)
  • No partial words, breathing, laughing, music or backgrounds sounds
  • An even speaking pace with a variety of words is best, like in interviews or audiobooks.

You can use FFmpeg to prepare your audio files, here are some examples:

# convert a multi-channel audio file to mono, set sample rate to 22050 hz, trim to 6 seconds, and output as WAV file.
ffmpeg -i input.mp3 -ac 1 -ar 22050 -t 6 -y me.wav
# use a simple noise filter to clean up audio, and select a start time start for sampling.
ffmpeg -i input.wav -af "highpass=f=200, lowpass=f=3000" -ac 1 -ar 22050 -ss 00:13:26.2 -t 6 -y me.wav
# A more complex noise reduction setup, including volume adjustment
ffmpeg -i input.mkv -af "highpass=f=200, lowpass=f=3000, volume=5, afftdn=nf=25" -ac 1 -ar 22050 -ss 00:13:26.2 -t 6 -y me.wav

Once your WAV file is prepared, save it in the /voices/ directory and update the config/voice_to_speaker.yaml file with the new file name.

For example:

...
tts-1-hd:
  me:
    model: xtts
    speaker: voices/me.wav # this could be you

Multilingual

Multilingual cloning support was added in version 0.11.0 and is available only with the XTTS v2 model. To use multilingual voices with piper simply download a language specific voice.

Coqui XTTSv2 has support for 16 languages: English (en), Spanish (es), French (fr), German (de), Italian (it), Portuguese (pt), Polish (pl), Turkish (tr), Russian (ru), Dutch (nl), Czech (cs), Arabic (ar), Chinese (zh-cn), Japanese (ja), Hungarian (hu) and Korean (ko).

Unfortunately the OpenAI API does not support language, but you can create your own custom speaker voice and set the language for that.

  1. Create the WAV file for your speaker, as in Custom Voices Howto
  2. Add the voice to config/voice_to_speaker.yaml and include the correct Coqui language code for the speaker. For example:
  xunjiang:
    model: xtts
    speaker: voices/xunjiang.wav
    language: zh-cn
  1. Don't remove high unicode characters in your config/pre_process_map.yaml! If you have these lines, you will need to remove them. For example:

Remove:

- - '[\U0001F600-\U0001F64F\U0001F300-\U0001F5FF\U0001F680-\U0001F6FF\U0001F700-\U0001F77F\U0001F780-\U0001F7FF\U0001F800-\U0001F8FF\U0001F900-\U0001F9FF\U0001FA00-\U0001FA6F\U0001FA70-\U0001FAFF\U00002702-\U000027B0\U000024C2-\U0001F251]+'
  - ''

These lines were added to the config/pre_process_map.yaml config file by default before version 0.11.0:

  1. Your new multi-lingual speaker voice is ready to use!

Custom Fine-Tuned Model Support

Adding a custom xtts model is simple. Here is an example of how to add a custom fine-tuned 'halo' XTTS model.

  1. Save the model folder under voices/ (all 4 files are required, including the vocab.json from the model)
openedai-speech$ ls voices/halo/
config.json  vocab.json  model.pth  sample.wav
  1. Add the custom voice entry under the tts-1-hd section of config/voice_to_speaker.yaml:
tts-1-hd:
...
  halo:
    model: halo # This name is required to be unique
    speaker: voices/halo/sample.wav # voice sample is required
    model_path: voices/halo
  1. The model will be loaded when you access the voice for the first time (--preload doesn't work with custom models yet)