🗣 Text to audio (TTS)
The /tts
endpoint can be used to generate speech from text.
Usage
Input: input
, model
For example, to generate an audio file, you can send a POST request to the /tts
endpoint with the instruction as the request body:
curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
"input": "Hello world",
"model": "tts"
}'
Returns an audio/wav
file.
Backends
🐸 Coqui
Required: Don’t use LocalAI
images ending with the -core
tag,. Python dependencies are required in order to use this backend.
Coqui works without any configuration, to test it, you can run the following curl command:
curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
"backend": "coqui",
"model": "tts_models/en/ljspeech/glow-tts",
"input":"Hello, this is a test!"
}'
Bark
Bark allows to generate audio from text prompts.
This is an extra backend - in the container is already available and there is nothing to do for the setup.
Model setup
There is nothing to be done for the model setup. You can already start to use bark. The models will be downloaded the first time you use the backend.
Usage
Use the tts
endpoint by specifying the bark
backend:
curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
"backend": "bark",
"input":"Hello!"
}' | aplay
To specify a voice from https://github.com/suno-ai/bark#-voice-presets ( https://suno-ai.notion.site/8b8e8749ed514b0cbf3f699013548683?v=bc67cff786b04b50b3ceb756fd05f68c ), use the model
parameter:
curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
"backend": "bark",
"input":"Hello!",
"model": "v2/en_speaker_4"
}' | aplay
Piper
To install the piper
audio models manually:
- Download Voices from https://github.com/rhasspy/piper/releases/tag/v0.0.2
- Extract the
.tar.tgz
files (.onnx,.json) insidemodels
- Run the following command to test the model is working
To use the tts endpoint, run the following command. You can specify a backend with the backend
parameter. For example, to use the piper
backend:
curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
"model":"it-riccardo_fasol-x-low.onnx",
"backend": "piper",
"input": "Ciao, sono Ettore"
}' | aplay
Note:
aplay
is a Linux command. You can use other tools to play the audio file.- The model name is the filename with the extension.
- The model name is case sensitive.
- LocalAI must be compiled with the
GO_TAGS=tts
flag.
Transformers-musicgen
LocalAI also has experimental support for transformers-musicgen
for the generation of short musical compositions. Currently, this is implemented via the same requests used for text to speech:
curl --request POST \
--url http://localhost:8080/tts \
--header 'Content-Type: application/json' \
--data '{
"backend": "transformers-musicgen",
"model": "facebook/musicgen-medium",
"input": "Cello Rave"
}' | aplay
Future versions of LocalAI will expose additional control over audio generation beyond the text prompt.
Vall-E-X
VALL-E-X is an open source implementation of Microsoft’s VALL-E X zero-shot TTS model.
Setup
The backend will automatically download the required files in order to run the model.
This is an extra backend - in the container is already available and there is nothing to do for the setup. If you are building manually, you need to install Vall-E-X manually first.
Usage
Use the tts endpoint by specifying the vall-e-x backend:
curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
"backend": "vall-e-x",
"input":"Hello!"
}' | aplay
Voice cloning
In order to use voice cloning capabilities you must create a YAML
configuration file to setup a model:
name: cloned-voice
backend: vall-e-x
parameters:
model: "cloned-voice"
vall-e:
# The path to the audio file to be cloned
# relative to the models directory
audio_path: "path-to-wav-source.wav"
Then you can specify the model name in the requests:
curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
"backend": "vall-e-x",
"model": "cloned-voice",
"input":"Hello!"
}' | aplay
Last updated 19 Jan 2024, 19:23 +0100 .