14 citations · 15 across the 3 of their papers we have counts for
5 papers · 1 filter
Local Topology Measures of Contextual Language Model Latent Spaces With Applications to Dialogue Term Extraction
Benjamin Matthias Ruppik, Michael Heck, Carel van Niekerk +5
A common approach for sequence tagging tasks based on contextual word representations is to train a machine learning classifier directly on these embedding vectors. This approach h…
Infusing Emotions into Task-oriented Dialogue Systems: Understanding, Management, and Generation
Shutong Feng, Hsien-chin Lin, Christian Geishauser +6
Emotions are indispensable in human communication, but are often overlooked in task-oriented dialogue (ToD) modelling, where the task success is the primary focus. While existing w…
From Chatter to Matter: Addressing Critical Steps of Emotion Recognition Learning in Task-oriented Dialogue
Shutong Feng, Nurul Lubis, Benjamin Ruppik +6
Emotion recognition in conversations (ERC) is a crucial task for building human-like conversational agents. While substantial efforts have been devoted to ERC for chit-chat dialogu…
EmoUS: Simulating User Emotions in Task-Oriented Dialogues
Hsien-Chin Lin, Shutong Feng, Christian Geishauser +6
Existing user simulators (USs) for task-oriented dialogue systems only model user behaviour on semantic and natural language levels without considering the user persona and emotion…
ChatGPT for Zero-shot Dialogue State Tracking: A Solution or an Opportunity?
Michael Heck, Nurul Lubis, Benjamin Ruppik +6
Recent research on dialogue state tracking (DST) focuses on methods that allow few- and zero-shot transfer to new domains or schemas. However, performance gains heavily depend on a…