2 citations · 4 across the 8 of their papers we have counts for
10 papers
Conditional Multi-Stage Failure Recovery for Embodied Agents
Youmna Farag, Svetlana Stoyanchev, Mohan Li +2
Embodied agents performing complex tasks are susceptible to execution failures, motivating the need for effective failure recovery mechanisms. In this work, we introduce a conditio…
WHISMA: A Speech-LLM to Perform Zero-shot Spoken Language Understanding
Mohan Li, Cong-Thanh Do, Simon Keizer +3
Speech large language models (speech-LLMs) integrate speech and text-based foundation models to provide a unified framework for handling a wide range of downstream tasks. In this p…
Semantic Map-based Generation of Navigation Instructions
Chengzu Li, Chao Zhang, Simone Teufel +2
We are interested in the generation of navigation instructions, either in their own right or as training material for robotic navigation task. In this paper, we propose a new appro…
Evaluating Large Language Models for Document-grounded Response Generation in Information-Seeking Dialogues
Norbert Braunschweiler, Rama Doddipatla, Simon Keizer +1
In this paper, we investigate the use of large language models (LLMs) like ChatGPT for document-grounded response generation in the context of information-seeking dialogues. For ev…
Adversarial learning of neural user simulators for dialogue policy optimisation
Simon Keizer, Caroline Dockes, Norbert Braunschweiler +2
Reinforcement learning based dialogue policies are typically trained in interaction with a user simulator. To obtain an effective and robust policy, this simulator should generate…
Opening up Minds with Argumentative Dialogues
Youmna Farag, Charlotte O. Brand, Jacopo Amidei +4
Recent research on argumentative dialogues has focused on persuading people to take some action, changing their stance on the topic of discussion, or winning debates. In this work,…
Dialogue Strategy Adaptation to New Action Sets Using Multi-dimensional Modelling
Simon Keizer, Norbert Braunschweiler, Svetlana Stoyanchev +1
A major bottleneck for building statistical spoken dialogue systems for new domains and applications is the need for large amounts of training data. To address this problem, we ado…
A study on cross-corpus speech emotion recognition and data augmentation
Norbert Braunschweiler, Rama Doddipatla, Simon Keizer +1
Models that can handle a wide range of speakers and acoustic conditions are essential in speech emotion recognition (SER). Often, these models tend to show mixed results when prese…
Towards Handling Unconstrained User Preferences in Dialogue
Suraj Pandey, Svetlana Stoyanchev, Rama Doddipatla
A user input to a schema-driven dialogue information navigation system, such as venue search, is typically constrained by the underlying database which restricts the user to specif…
Action State Update Approach to Dialogue Management
Svetlana Stoyanchev, Simon Keizer, Rama Doddipatla
Utterance interpretation is one of the main functions of a dialogue manager, which is the key component of a dialogue system. We propose the action state update approach (ASU) for…