1 citations · 3 across the 15 of their papers we have counts for
15 papers
Multilingual Idioms in Sentences and Conversations Across High-, Medium-, and Low-Resource Languages
Saeed Almheiri, Bilal Elbouardi, Salsabila Zahirah Pranida +16
Idiomatic expressions pose a major challenge for multilingual NLP because their meanings shift between figurative and literal usage, often requiring context for accurate interpreta…
Aligning Stuttered-Speech Research with End-User Needs: Scoping Review, Survey, and Guidelines
Hawau Olamide Toyin, Mutiah Apampa, Toluwani Aremu +6
Atypical speech is receiving greater attention in speech technology research, but much of this work unfolds with limited interdisciplinary dialogue. For stuttered speech in particu…
NADI 2025: The First Multidialectal Arabic Speech Processing Shared Task
Bashar Talafha, Hawau Olamide Toyin, Peter Sullivan +9
We present the findings of the sixth Nuanced Arabic Dialect Identification (NADI 2025) Shared Task, which focused on Arabic speech dialect processing across three subtasks: spoken…
Towards a Unified Benchmark for Arabic Pronunciation Assessment: Quranic Recitation as Case Study
Yassine El Kheir, Omnia Ibrahim, Amit Meghanani +12
We present a unified benchmark for mispronunciation detection in Modern Standard Arabic (MSA) using Qur'anic recitation as a case study. Our approach lays the groundwork for advanc…
Are LLMs Good Text Diacritizers? An Arabic and Yoruba Case Study
Hawau Olamide Toyin, Samar Mohamed Magdy, Hanan Aldarmaki
We investigate the effectiveness of large language models (LLMs) for text diacritization in two typologically distinct languages: Arabic and Yoruba. To enable a rigorous evaluation…
Clinical Annotations for Automatic Stuttering Severity Assessment
Ana Rita Valente, Rufael Marew, Hawau Olamide Toyin +6
Stuttering is a complex disorder that requires specialized expertise for effective assessment and treatment. This paper presents an effort to enhance the FluencyBank dataset with a…
ArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis
Hawau Olamide Toyin, Rufael Marew, Humaid Alblooshi +2
We introduce ArVoice, a multi-speaker Modern Standard Arabic (MSA) speech corpus with diacritized transcriptions, intended for multi-speaker speech synthesis, and can be useful for…
Voice of a Continent: Mapping Africa's Speech Technology Frontier
AbdelRahim Elmadany, Sang Yun Kwon, Hawau Olamide Toyin +3
Africa's rich linguistic diversity remains significantly underrepresented in speech technologies, creating barriers to digital inclusion. To alleviate this challenge, we systematic…
Infant Cry Detection Using Causal Temporal Representation
Minghao Fu, Danning Li, Aryan Gadhiya +8
This paper addresses a major challenge in acoustic event detection, in particular infant cry detection in the presence of other sounds and background noises: the lack of precise an…
Where Are We? Evaluating LLM Performance on African Languages
Ife Adebara, Hawau Olamide Toyin, Nahom Tesfu Ghebremichael +2
Africa's rich linguistic heritage remains underrepresented in NLP, largely due to historical policies that favor foreign languages and create significant data inequities. In this p…
All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages
Ashmal Vayani, Dinura Dissanayake, Hasindri Watawana +66
Existing Large Multimodal Models (LMMs) generally focus on only a few regions and languages. As LMMs continue to improve, it is increasingly important to ensure they understand cul…
Dialectal Coverage And Generalization in Arabic Speech Recognition
Amirbek Djanibekov, Hawau Olamide Toyin, Raghad Alshalan +2
Developing robust automatic speech recognition (ASR) systems for Arabic requires effective strategies to manage its diversity. Existing ASR systems mainly cover the modern standard…
STTATTS: Unified Speech-To-Text And Text-To-Speech Model
Hawau Olamide Toyin, Hao Li, Hanan Aldarmaki
Speech recognition and speech synthesis models are typically trained separately, each with its own set of learning objectives, training data, and model parameters, resulting in two…
Exploring the Limitations of Detecting Machine-Generated Text
Jad Doughman, Osama Mohammed Afzal, Hawau Olamide Toyin +3
Recent improvements in the quality of the generations by large language models have spurred research into identifying machine-generated text. Such work often presents high-performi…
ArTST: Arabic Text and Speech Transformer
Hawau Olamide Toyin, Amirbek Djanibekov, Ajinkya Kulkarni +1
We present ArTST, a pre-trained Arabic text and speech transformer for supporting open-source speech technologies for the Arabic language. The model architecture follows the unifie…