O
Osman Ramadan
Publications - 6
Citations - 1252
Osman Ramadan is an academic researcher. The author has contributed to research in topics: Deep learning & Semantic similarity. The author has an hindex of 5, co-authored 6 publications receiving 812 citations.
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MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling
Paweł Budzianowski,Tsung-Hsien Wen,Bo-Hsiang Tseng,Iñigo Casanueva,Stefan Ultes,Osman Ramadan,Milica Gasic +6 more
TL;DR: The Multi-Domain Wizard-of-Oz dataset (MultiWOZ) as discussed by the authors is a fully-labeled collection of human-human written conversations spanning over multiple domains and topics.
Proceedings ArticleDOI
MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling
Paweł Budzianowski,Tsung-Hsien Wen,Bo-Hsiang Tseng,Iñigo Casanueva,Stefan Ultes,Osman Ramadan,Milica Gasic +6 more
TL;DR: The Multi-Domain Wizard-of-Oz dataset (MultiWOZ), a fully-labeled collection of human-human written conversations spanning over multiple domains and topics is introduced, at a size of 10k dialogues, at least one order of magnitude larger than all previous annotated task-oriented corpora.
Proceedings ArticleDOI
Large-Scale Multi-Domain Belief Tracking with Knowledge Sharing
TL;DR: A novel approach is introduced that fully utilizes semantic similarity between dialogue utterances and the ontology terms, allowing the information to be shared across domains, and demonstrates great capability in handling multi-domain dialogues.
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Large-Scale Multi-Domain Belief Tracking with Knowledge Sharing
TL;DR: In this article, a novel approach is introduced that fully utilizes semantic similarity between dialogue utterances and the ontology terms, allowing the information to be shared across domains, and demonstrates great capability in handling multi-domain dialogues, simultaneously outperforming existing state-of-theart models in single-domain dialogue tracking tasks.
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Deep learning for language understanding of mental health concepts derived from Cognitive Behavioural Therapy
Lina Maria Rojas-Barahona,Bo-Hsiang Tseng,Yinpei Dai,Clare Mansfield,Osman Ramadan,Stefan Ultes,Michael Crawford,Milica Gasic +7 more
TL;DR: This work defines a mental health ontology based on the CBT principles, annotate a large corpus where this phenomena is exhibited and performs understanding using deep learning and distributed representations to significantly outperform non-deep-learning models in this difficult task.