metadata

language:
  - rw
pipeline_tag: text-to-speech
license: cc
tags:
  - TTS
  - Kinyarwanda
  - Text to speech

Model Description

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

Install the Coqui's TTS library:

pip install git+https://github.com/coqui-ai/TTS@0910cb76bcd85df56bf43654bb31427647cdfd0d#egg=TTS

Download the files from this repo, then run:

tts --text "text" --model_path model.pth --encoder_path SE_checkpoint.pth.tar --encoder_config_path config_se.json --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

[1] YourTTS paper [2] [Kinyarwanda TTS: Using a multi-speaker dataset to build a Kinyarwanda TTS model] (https://openreview.net/pdf?id=1gLgrqWnHF)