Communication difficulties following right hemisphere stroke : applying evidence to clinical management

Following reports in the 1960s that language may be affected by right hemisphere (RH) lesions, many limitations to effective communication in the right hemisphere damaged (RHD) population have been described and evidenced. However, stereotypical portrayals and descriptions of carefully selected cases may be misleading as to the extent of communication deficits. In many of the parameters in which RHD patients are presented as typically impaired, e.g. discourse skills, a less severe picture may emerge where data from the non-brain damaged (NBD) population are considered, with age and education variables controlled. Subsequent to RHD, some people show deficit on some communication measures, but many of these communication behaviours are also present in some NBD adults. Thus diagnosis of deficit must be made with reference both to the healthy peer population and the individual's pre-lesion behaviour. The authors' right RH stroke research programme includes studies of incidence of communication deficit, comparisons of RHD and NBD groups in various spoken discourse and comprehension tasks, comparison of RHD groups of different ages, detailed analysis of topic within discourse in RHD and NBD groups, family members' views of communication behaviour following RHD, and the natural course of communication change during the first year after RH stroke. The findings from several studies are summarised and used as the basis for management recommendations, which may guide future outcome research. There is an urgent need for the evaluation of communication management programmes, to determine whether therapists may with confidence offer an effective intervention service to those people whose communication skills are affected by RHD

Experimenting with the Gaze of a Conversational Agent

We have carried out a pilot experiment to investigate the effects of different eye gaze behaviors of a cartoon-like talking face on the quality of human-agent dialogues. We compared a version of the talking face that roughly implements some patterns of humanlike behavior with two other versions. We called this the optimal version. In one of the other versions the shifts in gaze were kept minimal and in the other version the shifts would occur randomly. The talking face has a number of restrictions. There is no speech recognition, so questions and replies have to\ud be typed in by the users of the systems. Despite this restriction we found that participants that conversed with the optimal agent appreciated the agent more than participants that conversed with the other agents. Conversations with the optimal version proceeded more efficiently. Participants needed less time to complete their task

On the simulation of interactive non-verbal behaviour in virtual humans

Development of virtual humans has focused mainly in two broad areas - conversational agents and computer game characters. Computer game characters have traditionally been action-oriented - focused on the game-play - and conversational agents have been focused on sensible/intelligent conversation. While virtual humans have incorporated some form of non-verbal behaviour, this has been quite limited and more importantly not connected or connected very loosely with the behaviour of a real human interacting with the virtual human - due to a lack of sensor data and no system to respond to that data. The interactional aspect of non-verbal behaviour is highly important in human-human interactions and previous research has demonstrated that people treat media (and therefore virtual humans) as real people, and so interactive non-verbal behaviour is also important in the development of virtual humans. This paper presents the challenges in creating virtual humans that are non-verbally interactive and drawing corollaries with the development history of control systems in robotics presents some approaches to solving these challenges - specifically using behaviour based systems - and shows how an order of magnitude increase in response time of virtual humans in conversation can be obtained and that the development of rapidly responding non-verbal behaviours can start with just a few behaviours with more behaviours added without difficulty later in development

Ethical Challenges in Data-Driven Dialogue Systems

The use of dialogue systems as a medium for human-machine interaction is an increasingly prevalent paradigm. A growing number of dialogue systems use conversation strategies that are learned from large datasets. There are well documented instances where interactions with these system have resulted in biased or even offensive conversations due to the data-driven training process. Here, we highlight potential ethical issues that arise in dialogue systems research, including: implicit biases in data-driven systems, the rise of adversarial examples, potential sources of privacy violations, safety concerns, special considerations for reinforcement learning systems, and reproducibility concerns. We also suggest areas stemming from these issues that deserve further investigation. Through this initial survey, we hope to spur research leading to robust, safe, and ethically sound dialogue systems.Comment: In Submission to the AAAI/ACM conference on Artificial Intelligence, Ethics, and Societ

Controlling the Gaze of Conversational Agents

We report on a pilot experiment that investigated the effects of different eye gaze behaviours of a cartoon-like talking face on the quality of human-agent dialogues. We compared a version of the talking face that roughly implements some patterns of human-like behaviour with\ud two other versions. In one of the other versions the shifts in gaze were kept minimal and in the other version the shifts would occur randomly. The talking face has a number of restrictions. There is no speech recognition, so questions and replies have to be typed in by the users\ud of the systems. Despite this restriction we found that participants that conversed with the agent that behaved according to the human-like patterns appreciated the agent better than participants that conversed with the other agents. Conversations with the optimal version also\ud proceeded more efficiently. Participants needed less time to complete their task

Measuring stress and cognitive load effects on the perceived quality of a multimodal dialogue system

In this paper we present the results of a pilot study investigating the impact of stress and cognitive load on the perceived interaction quality of a multimodal dialogue system for crisis management. Four test subjects interacted with the system in four differently configured trials aiming to induce low/high levels of stress and cognitive load. To measure the level of stress and cognitive load physiological sensors and subjective ratings were collected. After each trial the subjects filled in an evaluation questionnaire regarding the system interaction quality. In the end we conducted an in-depth interview with each subject. The trials were recorded with a webcam to facilitate the behaviour analysis. Results showed that both factors have an influence on the way subjects perceived the interaction quality, whereas the cognitive load seems to have a higher impact. Further quantitative experiments are needed in order to validate the results and quantify the weight of each factor. \u