10 citations · 30 across the 9 of their papers we have counts for
10 papers
Benchmarking and Domain Adaptation of Automatic Speech Recognition (ASR) for Adolescent Health Communication in Ghanaian Languages
Stephen E. Moore, Akwasi Asare, Mich-Seth Owusu +3
This paper presents an end-to-end study of automatic speech recognition (ASR) for adolescent health communication in three Ghanaian languages (Twi, Dagbani, and Ewe). The work proc…
DONDO: Open w2v-BERT Speech-Recognition Base Models for African Languages
Paul Azunre, Naafi Ibrahim, Joel Budu +1
We present DONDO, a family of open, permissively licensed automatic speech recognition (ASR) base models for African languages, built on the w2v-BERT 2.0 self-supervised speech enc…
Nsanku: Evaluating Zero-Shot Translation Performance of LLMs for Ghanaian Languages
Stephen E. Moore, Mich-Seth Owusu, Akwasi Asare +13
Large language models (LLMs) have demonstrated impressive multilingual capabilities for well-resourced languages, yet their performance on low-resource African languages remains po…
GhanaNLP Parallel Corpora: Comprehensive Multilingual Resources for Low-Resource Ghanaian Languages
Lawrence Adu Gyamfi, Paul Azunre, Stephen Edward Moore +4
Low resource languages present unique challenges for natural language processing due to the limited availability of digitized and well structured linguistic data. To address this g…
English-Twi Parallel Corpus for Machine Translation
Paul Azunre, Salomey Osei, Salomey Addo +24
We present a parallel machine translation training corpus for English and Akuapem Twi of 25,421 sentence pairs. We used a transformer-based translator to generate initial translati…
NLP for Ghanaian Languages
Paul Azunre, Salomey Osei, Salomey Addo +24
NLP Ghana is an open-source non-profit organization aiming to advance the development and adoption of state-of-the-art NLP techniques and digital language tools to Ghanaian languag…
Contextual Text Embeddings for Twi
Paul Azunre, Salomey Osei, Salomey Addo +24
Transformer-based language models have been changing the modern Natural Language Processing (NLP) landscape for high-resource languages such as English, Chinese, Russian, etc. Howe…
Using Deep Networks and Transfer Learning to Address Disinformation
Numa Dhamani, Paul Azunre, Jeffrey L. Gleason +4
We apply an ensemble pipeline composed of a character-level convolutional neural network (CNN) and a long short-term memory (LSTM) as a general tool for addressing a range of disin…
Semantic Classification of Tabular Datasets via Character-Level Convolutional Neural Networks
Paul Azunre, Craig Corcoran, Numa Dhamani +6
A character-level convolutional neural network (CNN) motivated by applications in "automated machine learning" (AutoML) is proposed to semantically classify columns in tabular data…
Abstractive Tabular Dataset Summarization via Knowledge Base Semantic Embeddings
Paul Azunre, Craig Corcoran, David Sullivan +4
This paper describes an abstractive summarization method for tabular data which employs a knowledge base semantic embedding to generate the summary. Assuming the dataset contains d…