no code implementations • 13 Nov 2023 • Guangzhi Sun, Shutong Feng, Dongcheng Jiang, Chao Zhang, Milica Gašić, Philip C. Woodland
Recently, advancements in large language models (LLMs) have shown an unprecedented ability across various language tasks.
no code implementations • 13 Oct 2023 • Carel van Niekerk, Christian Geishauser, Michael Heck, Shutong Feng, Hsien-Chin Lin, Nurul Lubis, Benjamin Ruppik, Renato Vukovic, Milica Gašić
Supervised neural approaches are hindered by their dependence on large, meticulously annotated datasets, a requirement that is particularly cumbersome for sequential tasks.
no code implementations • 22 Sep 2023 • Shutong Feng, Guangzhi Sun, Nurul Lubis, Chao Zhang, Milica Gašić
This study delves into the capacity of large language models (LLMs) to recognise human affect in conversations, with a focus on both open-domain chit-chat dialogues and task-oriented dialogues.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 24 Aug 2023 • Shutong Feng, Nurul Lubis, Benjamin Ruppik, Christian Geishauser, Michael Heck, Hsien-Chin Lin, Carel van Niekerk, Renato Vukovic, Milica Gašić
Our framework yields significant improvements for a range of chit-chat ERC models on EmoWOZ, a large-scale dataset for user emotion in ToDs.
no code implementations • 2 Jun 2023 • Hsien-Chin Lin, Shutong Feng, Christian Geishauser, Nurul Lubis, Carel van Niekerk, Michael Heck, Benjamin Ruppik, Renato Vukovic, Milica Gašić
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 emotions.
no code implementations • 2 Jun 2023 • Michael Heck, Nurul Lubis, Benjamin Ruppik, Renato Vukovic, Shutong Feng, Christian Geishauser, Hsien-Chin Lin, Carel van Niekerk, Milica Gašić
Recent research on dialogue state tracking (DST) focuses on methods that allow few- and zero-shot transfer to new domains or schemas.
no code implementations • SIGDIAL (ACL) 2022 • Nurul Lubis, Christian Geishauser, Hsien-Chin Lin, Carel van Niekerk, Michael Heck, Shutong Feng, Milica Gašić
They are ideally evaluated with human users, which however is unattainable to do at every iteration of the development phase.
no code implementations • SIGDIAL (ACL) 2022 • Hsien-Chin Lin, Christian Geishauser, Shutong Feng, Nurul Lubis, Carel van Niekerk, Michael Heck, Milica Gašić
In addition, its behaviour can be further shaped with reinforcement learning opening the door to training specialised user simulators.
no code implementations • COLING 2022 • Christian Geishauser, Carel van Niekerk, Nurul Lubis, Michael Heck, Hsien-Chin Lin, Shutong Feng, Milica Gašić
The lack of a framework with training protocols, baseline models and suitable metrics, has so far hindered research in this direction.
no code implementations • 7 Feb 2022 • Michael Heck, Nurul Lubis, Carel van Niekerk, Shutong Feng, Christian Geishauser, Hsien-Chin Lin, Milica Gašić
Our architecture and training strategies improve robustness towards sample sparsity, new concepts and topics, leading to state-of-the-art performance on a range of benchmarks.
no code implementations • 15 Sep 2021 • Christian Geishauser, Songbo Hu, Hsien-Chin Lin, Nurul Lubis, Michael Heck, Shutong Feng, Carel van Niekerk, Milica Gašić
The dialogue management component of a task-oriented dialogue system is typically optimised via reinforcement learning (RL).
1 code implementation • LREC 2022 • Shutong Feng, Nurul Lubis, Christian Geishauser, Hsien-Chin Lin, Michael Heck, Carel van Niekerk, Milica Gašić
We report a set of experimental results to show the usability of this corpus for emotion recognition and state tracking in task-oriented dialogues.
Ranked #1 on Emotion Recognition in Conversation on EmoWoz
Emotion Recognition in Conversation Task-Oriented Dialogue Systems
no code implementations • EMNLP 2021 • Carel van Niekerk, Andrey Malinin, Christian Geishauser, Michael Heck, Hsien-Chin Lin, Nurul Lubis, Shutong Feng, Milica Gašić
This highlights the importance of developing neural dialogue belief trackers that take uncertainty into account.
no code implementations • SIGDIAL (ACL) 2021 • Hsien-Chin Lin, Nurul Lubis, Songbo Hu, Carel van Niekerk, Christian Geishauser, Michael Heck, Shutong Feng, Milica Gašić
TUS can compete with rule-based user simulators on pre-defined domains and is able to generalise to unseen domains in a zero-shot fashion.