Search Results for author:
Found 36 papers, 6 papers with code
Learning to Read Maps: Understanding Natural Language Instructions from Unseen Maps
Robust situated dialog requires the ability to process instructions based on spatial information, which may or may not be available.
'What are you referring to?' Evaluating the Ability of Multi-Modal Dialogue Models to Process Clarificational Exchanges
Referential ambiguities arise in dialogue when a referring expression does not uniquely identify the intended referent for the addressee.
We are all Individuals: The Role of Robot Personality and Human Traits in Trustworthy Interaction
As robots take on roles in our society, it is important that their appearance, behaviour and personality are appropriate for the job they are given and are perceived favourably by the people with whom they interact.
Towards Explaining Autonomy with Verbalised Decision Tree States
To bridge this gap between in-mission robotic behaviours and operators' expectations, this work aims to provide a framework to explain decisions and actions taken by an autonomous vehicle during the mission, in an easy-to-understand manner.
Classification of Phonological Parameters in Sign Languages
Signers compose sign language phonemes that enable communication by combining phonological parameters such as handshape, orientation, location, movement, and non-manual features.
Unsupervised Sign Language Phoneme Clustering using HamNoSys Notation
Traditionally, sign language resources have been collected in controlled settings for specific tasks involving supervised sign classification or linguistic studies accompanied by specific annotation type.
Exploring Multi-Modal Representations for Ambiguity Detection & Coreference Resolution in the SIMMC 2.0 Challenge
Anaphoric expressions, such as pronouns and referential descriptions, are situated with respect to the linguistic context of prior turns, as well as, the immediate visual environment.
A Study of Automatic Metrics for the Evaluation of Natural Language Explanations
As transparency becomes key for robotics and AI, it will be necessary to evaluate the methods through which transparency is provided, including automatically generated natural language (NL) explanations.
The Lab vs The Crowd: An Investigation into Data Quality for Neural Dialogue Models
Challenges around collecting and processing quality data have hampered progress in data-driven dialogue models.
Transfer Learning for British Sign Language Modelling
Automatic speech recognition and spoken dialogue systems have made great advances through the use of deep machine learning methods.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Towards Large-Scale Data Mining for Data-Driven Analysis of Sign Languages
Access to sign language data is far from adequate.
Robots in the Danger Zone: Exploring Public Perception through Engagement
We describe the use of a light touch quiz-format survey instrument to integrate in-the-wild research participation into the engagement, allowing us to probe both the effectiveness of our engagement strategy, and public perceptions of the future roles of robots and humans working in dangerous settings, such as in the off-shore energy sector.
CRWIZ: A Framework for Crowdsourcing Real-Time Wizard-of-Oz Dialogues
Large corpora of task-based and open-domain conversational dialogues are hugely valuable in the field of data-driven dialogue systems.
Natural Language Interaction to Facilitate Mental Models of Remote Robots
Increasingly complex and autonomous robots are being deployed in real-world environments with far-reaching consequences.
Corpus of Multimodal Interaction for Collaborative Planning
As autonomous systems become more commonplace, we need a way to easily and naturally communicate to them our goals and collaboratively come up with a plan on how to achieve these goals.
Explainable Autonomy: A Study of Explanation Styles for Building Clear Mental Models
As unmanned vehicles become more autonomous, it is important to maintain a high level of transparency regarding their behaviour and how they operate.
The ORCA Hub: Explainable Offshore Robotics through Intelligent Interfaces
To enable this to happen, the remote operator will need a high level of situation awareness and key to this is the transparency of what the autonomous systems are doing and why.
MIRIAM: A Multimodal Chat-Based Interface for Autonomous Systems
We present MIRIAM (Multimodal Intelligent inteRactIon for Autonomous systeMs), a multimodal interface to support situation awareness of autonomous vehicles through chat-based interaction.
Explain Yourself: A Natural Language Interface for Scrutable Autonomous Robots
Autonomous systems in remote locations have a high degree of autonomy and there is a need to explain what they are doing and why in order to increase transparency and maintain trust.
A Review of Evaluation Techniques for Social Dialogue Systems
In contrast with goal-oriented dialogue, social dialogue has no clear measure of task success.
An Ensemble method for Content Selection for Data-to-text Systems
We present a novel approach for automatic report generation from time-series data, in the context of student feedback generation.
A Comparative Evaluation Methodology for NLG in Interactive Systems
We start with presenting a categorisation framework, giving an overview of different categories of evaluation measures, in order to provide standard terminology for categorising existing and new evaluation techniques.
