24 citations · 27 across the 10 of their papers we have counts for
7 papers · 1 filter
MultiHuSE: A Multimodal Dataset for Humour Styles and Emotions
Mary Ogbuka Kenneth, Foaad Khosmood, Abbas Edalat
Computational recognition of verbal humour remains a challenging task, requiring an understanding of language, delivery style, emotions, and cultural context. Most existing approac…
Detection of Self-Introductions in Legislative Testimony
Sofija Dimitrijevic, Pallavi Das, Kasey Liu +1
Self-introductions are common in legislative committee testimonies. Successfully detecting them and extracting the speaker's name is enormously helpful in the task of speaker ident…
Explaining Humour Style Classifications: An XAI Approach to Understanding Computational Humour Analysis
Mary Ogbuka Kenneth, Foaad Khosmood, Abbas Edalat
Humour styles can have either a negative or a positive impact on well-being. Given the importance of these styles to mental health, significant research has been conducted on their…
A Two-Model Approach for Humour Style Recognition
Mary Ogbuka Kenneth, Foaad Khosmood, Abbas Edalat
Humour, a fundamental aspect of human communication, manifests itself in various styles that significantly impact social interactions and mental health. Recognising different humou…
Exploring Description-Augmented Dataless Intent Classification
Ruoyu Hu, Foaad Khosmood, Abbas Edalat
In this work, we introduce several schemes to leverage description-augmented embedding similarity for dataless intent classification using current state-of-the-art (SOTA) text embe…
Systematic Literature Review: Computational Approaches for Humour Style Classification
Mary Ogbuka Kenneth, Foaad Khosmood, Abbas Edalat
Understanding various humour styles is essential for comprehending the multifaceted nature of humour and its impact on fields such as psychology and artificial intelligence. This u…