565 citations · 720 across the 43 of their papers we have counts for
13 papers · 1 filter
Measuring Research Progress and Linguistic Inclusion in Low-Resource Languages
Atnafu Lambebo Tonja, Tadesse Destaw Belay, Jesujoba Oluwadara Alabi +6
Large Language Models (LLMs) have accelerated research on low-resource and multilingual NLP, but their effectiveness in creating an equitable landscape remains unmapped. We analyze…
Ordered frequency in relatively hyperbolic groups
Dominic Bair
We study word frequencies along infinite strings whose finite prefixes lie in a regular language of geodesic representatives of group elements. Let \((G,\mathcal H)\) be a non-elem…
AfriGuard: Safety and Robust Refusal For African Languages
Israel Abebe Azime, Jesujoba O. Alabi, Iffat Maab +20
Large language models (LLMs) designed to interact with users are typically trained to respond appropriately to harmful or toxic content. However, ensuring appropriate responses bec…
Cultivar: A Contrastive and Locale-Oriented Translation Benchmark for Investigating Contamination and Localisation Robustness
Pinzhen Chen, Koel Dutta Chowdhury, Xiaoya Xu +20
Multilingual translation benchmarks are typically sourced in English and translated into other languages, treating language pairs as the unit of evaluation---a design that is prone…
From Monolingual to Multilingual: Evaluating Mamba for ASR in South African Languages
Jesujoba O. Alabi, Julian Herreilers, Badr M. Abdullah +1
Recent advances in automatic speech recognition (ASR) have explored different sequence models, including Conformer-based models and newer state space models such as Mamba. Although…
A Mechanistic Understanding of Pronoun Fidelity in LLMs
Katharina Trinley, Jesujoba O. Alabi, Dietrich Klakow +1
Faithful and robust pronoun use is important for fair and coherent generations, yet large language models largely fail when multiple referents use different pronouns. To study the…
OpenBibleTTS: Large-Scale Speech Resources and TTS Models for Low-Resource Languages
David Guzmán, Luel Hagos Beyene, Jesujoba Oluwadara Alabi +3
Recent advances in neural text-to-speech (TTS) and multilingual speech generation have substantially improved synthetic speech quality, yet these gains remain unevenly distributed…
AfrIFact: Cultural Information Retrieval, Evidence Extraction and Fact Checking for African Languages
Israel Abebe Azime, Jesujoba Oluwadara Alabi, Crystina Zhang +16
Assessing the veracity of a claim made online is a complex and important task with real-world implications. When these claims are directed at communities with limited access to inf…
Saar-Voice: A Multi-Speaker Saarbrücken Dialect Speech Corpus
Lena S. Oberkircher, Jesujoba O. Alabi, Dietrich Klakow +1
Natural language processing (NLP) and speech technologies have made significant progress in recent years; however, they remain largely focused on standardized language varieties. D…
YoNER: A New Yorùbá Multi-domain Named Entity Recognition Dataset
Peace Busola Falola, Jesujoba O. Alabi, Solomon O. Akinola +3
Named Entity Recognition (NER) is a foundational NLP task, yet research in Yorùbá has been constrained by limited and domain-specific resources. Existing resources, such as Masakha…
Ethio-ASR: Joint Multilingual Speech Recognition and Language Identification for Ethiopian Languages
Badr M. Abdullah, Israel Abebe Azime, Atnafu Lambebo Tonja +14
We present Ethio-ASR, a suite of multilingual CTC-based automatic speech recognition (ASR) models jointly trained on five Ethiopian languages: Amharic, Tigrinya, Oromo, Sidaama, an…
Afri-MCQA: Multimodal Cultural Question Answering for African Languages
Atnafu Lambebo Tonja, Srija Anand, Emilio Villa-Cueva +16
Africa is home to over one-third of the world's languages, yet remains underrepresented in AI research. We introduce Afri-MCQA, the first Multilingual Cultural Question-Answering b…
CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data
Pedro Ortiz Suarez, Laurie Burchell, Catherine Arnett +94
Language identification (LID) is a fundamental step in curating multilingual corpora. However, LID models still perform poorly for many languages, especially on the noisy and heter…