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# Few-Shot Voice Cloning | |
This repository is an implementation of the pipeline for few-short voice cloning based on SpeechT5 architecture introduced in [ SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing](https://arxiv.org/abs/2110.07205). | |
It is able to clone a voice from 15-30 seconds of audio recording in English (another languages are planned). | |
# Getting Started | |
Clone repository | |
```angular2html | |
git clone https://github.com/konverner/deep-voice-cloning.git | |
``` | |
Install the modules | |
```angular2html | |
pip install . | |
``` | |
Run traning specifying arguments using config file `training_config.json` or the console command, for example | |
```angular2html | |
python scripts/train.py --audio_path scripts/input/hank.mp3 --output_dir /content/deep-voice-cloning/models | |
``` | |
Resulting model will be saved in `output_dir` directory. It will be used in the next step. | |
Run inference specifying arguments using config file `inference_config.json` or the console command, for example | |
```angular2html | |
python scripts/cloning_inference.py --model_path "/content/deep-voice-cloning/models/microsoft_speecht5_tts_hank"\ | |
--input_text 'do the things, not because they are easy, but because they are hard'\ | |
--output_path "scripts/output/do_the_things.wav" | |
``` | |
Resulting audio file will be saved as `output_path` file. |