Search Results for author:
Found 8 papers, 6 papers with code
MasakhaPOS: Part-of-Speech Tagging for Typologically Diverse African Languages
In this paper, we present MasakhaPOS, the largest part-of-speech (POS) dataset for 20 typologically diverse African languages.
MasakhaNEWS: News Topic Classification for African languages
Furthermore, we explore several alternatives to full fine-tuning of language models that are better suited for zero-shot and few-shot learning such as cross-lingual parameter-efficient fine-tuning (like MAD-X), pattern exploiting training (PET), prompting language models (like ChatGPT), and prompt-free sentence transformer fine-tuning (SetFit and Cohere Embedding API).
MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition
African languages are spoken by over a billion people, but are underrepresented in NLP research and development.
BibleTTS: a large, high-fidelity, multilingual, and uniquely African speech corpus
BibleTTS is a large, high-quality, open speech dataset for ten languages spoken in Sub-Saharan Africa.
The Makerere Radio Speech Corpus: A Luganda Radio Corpus for Automatic Speech Recognition
Building a usable radio monitoring automatic speech recognition (ASR) system is a challenging task for under-resourced languages and yet this is paramount in societies where radio is the main medium of public communication and discussions.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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A Few Thousand Translations Go a Long Way! Leveraging Pre-trained Models for African News Translation
We focus on two questions: 1) How can pre-trained models be used for languages not included in the initial pre-training?
MasakhaNER: Named Entity Recognition for African Languages
We take a step towards addressing the under-representation of the African continent in NLP research by creating the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages, bringing together a variety of stakeholders.
Keyword Spotter Model for Crop Pest and Disease Monitoring from Community Radio Data
In societies with well developed internet infrastructure, social media is the leading medium of communication for various social issues especially for breaking news situations.
