https://github.com/egorsmkv/radtts-uk
🇺🇦 Ukrainian RAD-TTS++ models (decoder + models with 3 voices) and HiFiGAN model
https://github.com/egorsmkv/radtts-uk
conversational-ai hifigan speech-ai speech-synthesis text-to-speech tts ukrainian vocoder
Last synced: 8 months ago
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🇺🇦 Ukrainian RAD-TTS++ models (decoder + models with 3 voices) and HiFiGAN model
- Host: GitHub
- URL: https://github.com/egorsmkv/radtts-uk
- Owner: egorsmkv
- License: apache-2.0
- Created: 2023-05-18T20:13:20.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-02-27T01:26:50.000Z (9 months ago)
- Last Synced: 2025-02-27T02:33:05.037Z (9 months ago)
- Topics: conversational-ai, hifigan, speech-ai, speech-synthesis, text-to-speech, tts, ukrainian, vocoder
- Homepage: https://huggingface.co/Yehor/radtts-uk
- Size: 25.4 KB
- Stars: 4
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# 🇺🇦 Ukrainian RADTTS/RADTTS++ models and HiFiGAN model
Join our Speech Synthesis Group in Telegram: https://t.me/speech_synthesis_uk
Donate: https://send.monobank.ua/jar/3Saxixsdua
## Demo
Hugging Face space:
https://huggingface.co/spaces/Yehor/radtts-uk-demo
## Overview
This repository contains links to models:
- Decoder model for RADTTS
- Decoder model for RADTTS++
- Pretrained model for RADTTS
- Pretrained model for RADTTS++ with AGAP config
- Pretrained model for RADTTS++ with BGAP config
- Pretrained model for RADTTS++ with DAP config
Voices are from [Open Source Ukrainian Text-to-Speech datasets](https://github.com/egorsmkv/ukrainian-tts-datasets)
These models have three voices:
- Lada
- Tetiana
- Mykyta
## Demo
### Lada
https://github.com/egorsmkv/radtts-uk/assets/7875085/ee89bc98-f425-4533-9404-5124ddc8e92c
### Tetiana
https://github.com/egorsmkv/radtts-uk/assets/7875085/88d29b0d-5f78-403d-be51-765444e53950
### Mykyta
https://github.com/egorsmkv/radtts-uk/assets/7875085/96d412b1-8977-48ed-93d0-6b741d6014ba
## How to run?
Clone the repository https://github.com/egorsmkv/radtts and run the following command:
```
python inference.py -c config.json -r models/model_dap_84000.pt -v hifigan.pt -k hifigan_config.json \
-t test.txt -s lada --speaker_attributes lada --speaker_text lada -o results
```
## Download
Dropbox link to all models: https://www.dropbox.com/scl/fo/0eoipxgk16o2cnw2ymba3/h?dl=0&rlkey=7trclhuzuo6xno5n06xg4z7gd
### Acknowledgement
- Dmytro Chaplynskyi [@dchaplinsky](https://github.com/dchaplinsky): help with access to UCU's cluster
- Decoder model for RADTTS++ and Pretrained model for RADTTS++ with DAP config have been trained on the Cluster of Excellence UCU/[Lang-uk](https://github.com/lang-uk).