9 citations · 17 across the 4 of their papers we have counts for
4 papers
Lexical Tone is Hard to Quantize: Probing Discrete Speech Units in Mandarin and Yorùbá
Opeyemi Osakuade, Simon King
Discrete speech units (DSUs) are derived by quantising representations from models trained using self-supervised learning (SSL). They are a popular representation for a wide variet…
Do Discrete Self-Supervised Representations of Speech Capture Tone Distinctions?
Opeyemi Osakuade, Simon King
Discrete representations of speech, obtained from Self-Supervised Learning (SSL) foundation models, are widely used, especially where there are limited data for the downstream task…
Sign-to-Speech Model for Sign Language Understanding: A Case Study of Nigerian Sign Language
Steven Kolawole, Opeyemi Osakuade, Nayan Saxena +1
Through this paper, we seek to reduce the communication barrier between the hearing-impaired community and the larger society who are usually not familiar with sign language in the…
NaijaNER : Comprehensive Named Entity Recognition for 5 Nigerian Languages
Wuraola Fisayo Oyewusi, Olubayo Adekanmbi, Ifeoma Okoh +5
Most of the common applications of Named Entity Recognition (NER) is on English and other highly available languages. In this work, we present our findings on Named Entity Recognit…