Helen Hastie

Helen Hastie
Heriot-Watt University · School of Mathematical and Computer Sciences

Ph.D.

About

146
Publications
14,738
Reads
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1,581
Citations
Additional affiliations
October 2009 - present
Heriot-Watt University
Position
  • Lecturer
October 2009 - present
Heriot-Watt University
Position
  • Associate Professor (Reader)

Publications

Publications (146)
Conference Paper
Full-text available
Incremental processing allows system designers to address several discourse phenomena that have previously been somewhat neglected in interactive systems, such as backchannels or barge-ins, but that can enhance the responsiveness and naturalness of systems. Unfortunately, prior work has focused largely on deterministic incremental decision making,...
Preprint
Full-text available
Signers compose sign language phonemes that enable communication by combining phonological parameters such as handshape, orientation, location, movement, and non-manual features. Linguistic research often breaks down signs into their constituent parts to study sign languages and often a lot of effort is invested into the annotation of the videos. I...
Preprint
Full-text available
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. To date, very few who explored signing videos found online on social media platforms as well as the use of unsupervised methods applied to such r...
Preprint
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. However, a speaker's referential descriptions do not always uniquely identify the referent, leading to ambiguities in need of resolution through subsequent clarificat...
Conference Paper
Full-text available
Automated planning provides the tools for intelligent behaviours in robotic platforms deployed in real-world environments. The complexity of these domains requires planning models that support the system's dynamics. This results in AI planning approaches often generating plans where the reasoning around the solution remains obscure for the operator...
Article
Full-text available
This paper describes IEEE P7001, a new draft standard on transparency of autonomous systems 1 . In the paper, we outline the development and structure of the draft standard. We present the rationale for transparency as a measurable, testable property. We outline five stakeholder groups: users, the general public and bystanders, safety certification...
Poster
Full-text available
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. Here, we explore parallels between the generation of such explanations and the much-studied field of evaluation of Natural Language Generation (NL...
Preprint
Full-text available
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. Here, we explore parallels between the generation of such explanations and the much-studied field of evaluation of Natural Language Generation (NL...
Preprint
Full-text available
Challenges around collecting and processing quality data have hampered progress in data-driven dialogue models. Previous approaches are moving away from costly, resource-intensive lab settings, where collection is slow but where the data is deemed of high quality. The advent of crowd-sourcing platforms, such as Amazon Mechanical Turk, has provided...
Preprint
Full-text available
Access to sign language data is far from adequate. We show that it is possible to collect the data from social networking services such as TikTok, Instagram, and YouTube by applying data filtering to enforce quality standards and by discovering patterns in the filtered data, making it easier to analyse and model. Using our data collection pipeline,...
Preprint
Full-text available
Automatic speech recognition and spoken dialogue systems have made great advances through the use of deep machine learning methods. This is partly due to greater computing power but also through the large amount of data available in common languages, such as English. Conversely, research in minority languages, including sign languages, is hampered...
Preprint
Full-text available
Public perceptions of Robotics and Artificial Intelligence (RAI) are important in the acceptance, uptake, government regulation and research funding of this technology. Recent research has shown that the public's understanding of RAI can be negative or inaccurate. We believe effective public engagement can help ensure that public opinion is better...
Conference Paper
Full-text available
Transparency is an important factor for robots, autonomous systems and AI, if they are to be adopted into our lives and society at large. Explanations are one way to provide such transparency and natural language explanations are a clear and intuitive way to do this, helping users to understand what a robot or AI is doing and why. In this abstract,...
Preprint
Full-text available
Increasingly complex and autonomous robots are being deployed in real-world environments with far-reaching consequences. High-stakes scenarios, such as emergency response or offshore energy platform and nuclear inspections, require robot operators to have clear mental models of what the robots can and can't do. However, operators are often not the...
Preprint
Large corpora of task-based and open-domain conversational dialogues are hugely valuable in the field of data-driven dialogue systems. Crowdsourcing platforms, such as Amazon Mechanical Turk, have been an effective method for collecting such large amounts of data. However, difficulties arise when task-based dialogues require expert domain knowledge...
Conference Paper
Full-text available
Autonomous vehicles and robots are increasingly being deployed to remote, dangerous environments in the energy sector, search and rescue and the military. As a result, there is a need for humans to interact with these robots to monitor their tasks, such as inspecting and repairing offshore wind-turbines. Conversational Agents can improve situation...
Preprint
Full-text available
Collaboration between human supervisors and remote teams of robots is highly challenging, particularly in high-stakes, distant, hazardous locations, such as off-shore energy platforms. In order for these teams of robots to truly be beneficial, they need to be trusted to operate autonomously, performing tasks such as inspection and emergency respons...
Conference Paper
Full-text available
The field of Explainable Artificial Intelligence attempts to solve the problem of algorithmic opacity. Many terms and notions have been introduced recently to define Explainable AI, however, these terms seem to be used interchangeably, which is leading to confusion in this rapidly expanding field. As a solution to overcome this problem, we present...
Preprint
Full-text available
Autonomous underwater vehicles (AUVs) are being tasked with increasingly complex missions. The acoustic communications required for AUVs are, by the nature of the medium, low bandwidth while adverse environmental conditions underwater often mean they are also intermittent. This has motivated development of highly autonomous systems, which can opera...
Conference Paper
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. This is particularly important in hazardous, high-risk scenarios. Here, we describe a multimodal interface, MIRIAM, that enables remote vehicle behaviour to be queri...
Conference Paper
Full-text available
Autonomous systems are designed to carry out activities in remote, hazardous environments without the need for operators to micro-manage them. It is, however, essential that operators maintain situation awareness in order to monitor vehicle status and handle unforeseen circumstances that may affect their intended behaviour, such as a change in the...
Article
Full-text available
We present the UK Robotics and Artificial Intelligence Hub for Offshore Robotics for Certification of Assets (ORCA Hub), a 3.5 year EPSRC funded, multi-site project. The ORCA Hub vision is to use teams of robots and autonomous intelligent systems (AIS) to work on offshore energy platforms to enable cheaper, safer and more efficient working practice...
Article
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. Here, we describe a natural language chat interface that enables vehicle behaviour to be queried by the user. We obtain an interpretable model of autonomy through havi...
Chapter
In the past 10 years, very few published studies include some kind of extrinsic evaluation of an NLG component in an end-to-end-system, be it for phone or mobile-based dialogues or social robotic interaction. This may be attributed to the fact that these types of evaluations are very costly to set-up and run for a single component. The question the...
Conference Paper
For autonomous systems to be accepted by society and operators, they have to instil the appropriate level of trust. In this paper, we discuss what dimensions constitute trust and examine certain triggers of trust for an autonomous underwater vehicle, comparing a multimodal command and control interface with a language-only reporting system. We conc...
Conference Paper
Full-text available
We present MIRIAM (Multimodal Intelligent inteRactIon for Autonomous systeMs), a multimodal interface to support situation awareness of autonomous vehicles through chat-based interaction. The user is able to chat about the vehicle's plan, objectives, previous activities and mission progress. The system is mixed initiative in that it pro-actively se...
Conference Paper
Full-text available
Robot embodiment is, by its very nature, holistic and understanding how various aspects contribute to the user perception of the robot is non-trivial. A study is presented here that investigates whether there is an interaction effect between voice and other aspects of embodiment, such as movement and appearance, in a pedagogical setting. An on-line...
Article
Full-text available
In contrast with goal-oriented dialogue, social dialogue has no clear measure of task success. Consequently, evaluation of these systems is notoriously hard. In this paper, we review current evaluation methods, focusing on automatic metrics. We conclude that turn-based metrics often ignore the context and do not account for the fact that several re...
Conference Paper
Human and robot tutors alike have to give careful consideration as to how feedback is delivered to students to provide a motivating yet clear learning context. Here, we performed a perception study to investigate attitudes towards negative and positive robot feedback in terms of perceived emotional valence on the dimensions of ‘Pleasantness’, ‘Poli...
Conference Paper
A prototype will be demonstrated that takes activity and sensor data from Autonomous Underwater Vehicles (AUVs) and automatically generates multimodal output in the form of mission reports containing natural language and visual elements. Specifically, the system takes time-series sensor data, mission logs, together with mission plans as its input,...
Conference Paper
Full-text available
In the past 10 years, only around 15% of published conference papers include some kind of extrinsic evaluation of an NLG component in an end-to-end system. These types of evaluations are costly to setup and run, so is it worth it? Is there anything to be gained over and above intrinsic quality measures obtained in off-line experiments? In this pape...
Article
Full-text available
Incremental dialogue systems are often perceived as more responsive and natural because they are able to address phenomena of turn-taking and overlapping speech, such as backchannels or barge-ins. Previous work in this area has often identified distinctive prosodic features, or features relating to syntactic or semantic completeness, as marking app...
Conference Paper
Full-text available
Within any learning process, the formation of a socio-emotional relationship between learner and teacher is paramount to facilitating a good learning experience. The ability to form this relationship may come naturally to an attentive teacher; but how do we endow an unemotional robot with this ability? In this paper, we extend upon insights from th...
Conference Paper
Full-text available
We explore the effect of the feedback strategy used by a virtual robot agent in the context of a real-world treasure-hunt activity carried out by children aged 11–12. We compare two versions of a tablet-based virtual robot agent, which provides either neutral or affective feedback during the treasure hunt. The results suggest that the use of the ta...
Conference Paper
Full-text available
Navigation when running is exploratory, characterised by both starting and ending in the same location, and iteratively foraging the environment to find areas with the most suitable running conditions. Runners do not wish to be explicitly directed , or refer to navigation aids that cause them to stop running, such as maps. Such undirected navigatio...
Conference Paper
Full-text available
We present a novel approach for automatic report generation from time-series data, in the context of student feedback generation. Our proposed methodology treats content selection as a multi-label classification (MLC) problem, which takes as input time-series data (students' learning data) and outputs a summary of these data (feedback). Unlike prev...
Conference Paper
Full-text available
We present an autonomous empathic robotic tutor to be used in classrooms as a peer in a virtual learning environment. The system merges a virtual agent design with HRI features, consisting of a robotic embodiment, a multimedia interactive learning application and perception sensors that are controlled by an artificial intelligence agent.
Conference Paper
Full-text available
This position paper describes the potential for data-to-text generation for military applications and the associated challenges in terms of user interaction, system development and deployment. We also present a use-case for a prototype system for debrief generation for autonomous underwater vehicles (AUVs).
Conference Paper
Work on training semantic slot labellers for use in Natural Language Processing applications has typically either relied on large amounts of labelled input data, or has assumed entirely unlabelled inputs. The former technique tends to be costly to apply, while the latter is often not as accurate as its supervised counterpart. Here, we present a sem...
Conference Paper
Full-text available
We explore the effect of the behaviour of a virtual robot agent in the context of a real-world treasure-hunt activity carried out by children aged 11-12. We compare three conditions: a traditional paper-based treasure hunt, along with a virtual robot on a tablet which provides either neutral or affective feedback during the treasure hunt. The initi...
Conference Paper
Full-text available
In this paper, we describe the results of an interview study conducted across several European countries on teachers' views on the use of empathic robotic tutors in the classroom. The main goals of the study were to elicit teachers' thoughts on the integration of the robotic tutors in the daily school practice, understanding the main roles that the...
Conference Paper
Full-text available
There has been some studies in applying robots to education and recent research on socially intelligent robots show robots as partners that collaborate with people. On the other hand, serious games and interaction technologies have also proved to be important pedagogical tools, enhancing collaboration and interest in the learning process. This pape...
Conference Paper
Full-text available
We present a novel approach for automatic report generation from time-series data, in the context of student feedback generation. Our proposed methodology treats content selection as a multi-label (ML) classification problem, which takes as input time-series data and outputs a set of templates, while capturing the dependencies between selected temp...
Conference Paper
There are several challenges in applying conversational social robots to Technology Enhanced Learning and Serious Gaming. In this paper, we focus in particular on the dialogue management issues in building an empathic robotic tutor that plays a multi-person serious game with students to help them learn and understand the underlying educational conc...