🌅
🌅
Old Age
YAD: Leveraging T5 for Improved Automatic Diacritization of Yorùbá Text
December 28, 2024 · Declared Dead · 🏛 arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Akindele Michael Olawole, Jesujoba O. Alabi, Aderonke Busayo Sakpere, David I. Adelani
arXiv ID
2412.20218
Category
cs.CL: Computation & Language
Citations
3
Venue
arXiv.org
Last Checked
5 months ago
Abstract
In this work, we present Yorùbá automatic diacritization (YAD) benchmark dataset for evaluating Yorùbá diacritization systems. In addition, we pre-train text-to-text transformer, T5 model for Yorùbá and showed that this model outperform several multilingually trained T5 models. Lastly, we showed that more data and larger models are better at diacritization for Yorùbá
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
📜 Similar Papers
In the same crypt — Computation & Language
🌅
🌅
Old Age
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
🌅
🌅
Old Age
XLNet: Generalized Autoregressive Pretraining for Language Understanding
🔮
🔮
The Ethereal
Effective Approaches to Attention-based Neural Machine Translation
🌅
🌅
Old Age
A large annotated corpus for learning natural language inference
🌅
🌅
Old Age
HellaSwag: Can a Machine Really Finish Your Sentence?
Died the same way — 👻 Ghosted
R.I.P.
👻
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
👻
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
👻
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
👻
Ghosted