Kinyarwanda TTS: Using a Multi-Speaker Dataset to Build a Kinyarwanda TTS Model
Abstract
The field of text-to-speech (TTS) technology has been rapidly advancing in recent years, and has become an increasingly important aspect of our lives. This presents an opportunity for Africa, especially in facilitating access to information to many vulnerable socio-economic groups. However, the lack of availability of high-quality datasets is a major hindrance. In this work, we create a dataset based on recordings of the Bible. Using an existing Kinyarwanda speech-to-text model we were able to segment and align the speech and the text, and then created a multi-speaker Kinyarwanda TTS model.
Cite
Text
Rutunda et al. "Kinyarwanda TTS: Using a Multi-Speaker Dataset to Build a Kinyarwanda TTS Model." ICLR 2023 Workshops: AfricaNLP, 2023.Markdown
[Rutunda et al. "Kinyarwanda TTS: Using a Multi-Speaker Dataset to Build a Kinyarwanda TTS Model." ICLR 2023 Workshops: AfricaNLP, 2023.](https://mlanthology.org/iclrw/2023/rutunda2023iclrw-kinyarwanda/)BibTeX
@inproceedings{rutunda2023iclrw-kinyarwanda,
title = {{Kinyarwanda TTS: Using a Multi-Speaker Dataset to Build a Kinyarwanda TTS Model}},
author = {Rutunda, Samuel and Kabanda, Kleber and Stan, Adriana},
booktitle = {ICLR 2023 Workshops: AfricaNLP},
year = {2023},
url = {https://mlanthology.org/iclrw/2023/rutunda2023iclrw-kinyarwanda/}
}