| | --- |
| | language: |
| | - rw |
| | pipeline_tag: text-to-speech |
| | --- |
| | |
| |
|
| |
|
| | ## 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). Due to its zero-shot learning capabilities, new voices can be introduced with 1min speech. |
| | The model was trained using the Coqui's TTS library, and the YourTTS[1] architecture. It was trained on 67 hours of Kinyarwanda bible data, for 100 epochs. |
| |
|
| |
|
| | ## Data Sources |
| |
|
| | <!-- Provide the basic links for the model. --> |
| |
|
| | - **Audio data:** [www.faithcomesbyhearing.com, version -> Common Language Version audio Old Testament] |
| | - **Text data:** [www.bible.com, version -> Bibiliya Ijambo ry'imana(BIR)(only the Old Testament was used)] |
| |
|
| | # 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 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 |
| | <!-- 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) |
| | |
