File size: 1,307 Bytes
9bf3fe4 5883c3d 9bf3fe4 06b4e61 9bf3fe4 06b4e61 9bf3fe4 393ee20 89a623f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 |
---
language:
- rw
pipeline_tag: text-to-speech
tags:
- TTS
- Kinyarwanda
- Text to speech
license: cc-by-sa-4.0
---
## Model Description
<!-- Provide a longer summary of what this model is. -->
This model is an end-to-end deep-learning-based Kinyarwanda Text-to-Speech (TTS). The model was trained using the Coqui's TTS library, and the YourTTS[1] architecture.
# Usage
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
Install the Coqui's TTS library:
```
pip install TTS
```
Download the files from this repo, then run:
```
tts --text "text" --model_path model.pth --config_path config.json --speakers_file_path speakers.pth --speaker_wav conditioning_audio.wav --out_path out.wav
```
Where the conditioning audio is a wav file(s) to condition a multi-speaker TTS model with a Speaker Encoder, you can give multiple file paths. The d_vectors is computed as their average.
# References
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information should go in this section. -->
[1] [YourTTS paper](https://arxiv.org/pdf/2112.02418.pdf)
[2] [Kinyarwanda TTS: Using a multi-speaker dataset to build a Kinyarwanda TTS model](https://openreview.net/pdf?id=1gLgrqWnHF) |