ML Anthology

VoxMg: An Automatic Speech Recognition Dataset for Malagasy

Falia Ramanantsoa
ICLRW 2023
/iclrw/2023/ramanantsoa2023iclrw-voxmg/

Abstract

African languages are not well-represented in Natural Language Processing (NLP). The main reason is a lack of resources for training models. Low-resource languages, such as Malagasy, cannot benefit from modern NLP methods if no datasets are available. This paper presents the curation and annotation of VoxMg, a speech dataset for Malagasy that consists of 3873 audio files totaling 10.80 hours. We also run a baseline, which is the first Automatic Speech Recognition (ASR) model ever built in this language and obtained a Word Error Rate (WER) of 33%

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Cite

Text

Ramanantsoa. "VoxMg: An Automatic Speech Recognition Dataset for Malagasy." ICLR 2023 Workshops: AfricaNLP, 2023.

Markdown

[Ramanantsoa. "VoxMg: An Automatic Speech Recognition Dataset for Malagasy." ICLR 2023 Workshops: AfricaNLP, 2023.](https://mlanthology.org/iclrw/2023/ramanantsoa2023iclrw-voxmg/)

BibTeX

@inproceedings{ramanantsoa2023iclrw-voxmg,
  title     = {{VoxMg: An Automatic Speech Recognition Dataset for Malagasy}},
  author    = {Ramanantsoa, Falia},
  booktitle = {ICLR 2023 Workshops: AfricaNLP},
  year      = {2023},
  url       = {https://mlanthology.org/iclrw/2023/ramanantsoa2023iclrw-voxmg/}
}