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Keane, Mark T.
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Keane, Mark T.
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Keane, Mark T.
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Now showing 1 - 7 of 7
- PublicationThe effect of soft, modal and loud voice levels on entrainment in noisy conditionsConversation partners have a tendency to adapt their vocal intensity to each other and to other social and environmental factors. A socially adequate vocal intensity level by a speech synthesiser that goes beyond mere volume adjustment is highly desirable for a rewarding and successful human-machine or machine mediated human-human interaction. This paper examines the interaction of the Lombard effect and speaker entrainment in a controlled experiment conducted with a confederate interlocutor. The interlocutor was asked to maintain either a soft, a modal or a loud voice level during the dialogues. Through half of the trials, subjects were exposed to a cocktail party noise through headphones. The analytical results suggest that both the background noise and the interlocutors voice level affect the dynamics of speaker entrainment. Speakers appear to still entrain to the voice level of their interlocutor in noisy conditions, though to a lesser extent, as strategies of ensuring intelligibility affect voice levels as well. These findings could be leveraged in spoken dialogue systems and speech generating devices to help choose a vocal effort level for the synthetic voice that is both intelligible and socially suited to a specific interaction.
170 - PublicationRe-reading the Ryan report: Witnessing via close and distant readingIn the days following the publication of the Final Report of the Commission to Inquire into Child Abuse (2009), also known as the Ryan Report, there was widespread national and international public reaction to the conclusions of the report that over the course of nine decades abuse had been severe and systemic in the Irish residential-institution system for children run by the religious congregations of the Catholic church.
493Scopus© Citations 7 - PublicationWhy some surprises are more surprising than others: Surprise as a metacognitive sense of explanatory difficultyEarly theories of surprise, including Darwin's, argued that it was predominantly a basic emotion. Recently, theories have taken a more cognitive view of surprise, casting it as a process of 'making sense of surprising events'. The current paper advances the view that the essence of this sense-making process is explanation; specifically, that people's perception of surprise is a metacognitive estimate of the cognitive work involved in explaining an abnormal event. So, some surprises are more surprising because they are harder to explain. This proposal is tested in eight experiments that explore how (i) the contents of memory can influence surprise, (ii) different classes of scenarios can retrieve more/less relevant knowledge from memory to explain surprising outcomes, (iii) how partial explanations constrain the explanation process, reducing surprise, and (iv) how, overall, any factor that acts to increase the cognitive work in explaining a surprising event, results in higher levels of surprise (e.g., task demands to find three rather than one explanations). Across the present studies, using different materials, paradigms and measures, it is consistently and repeatedly found that the difficulty of explaining a surprising outcome is the best predictor for people’s perceptions of the surprisingness of events. Alternative accounts of these results are considered, as are future directions for this research.
2390Scopus© Citations 71 - PublicationThe Role of Surprise in Learning: Different Surprising Outcomes Affect Memorability DifferentiallySurprise has been explored as a cognitive‐emotional phenomenon that impacts many aspects of mental life from creativity to learning to decision‐making. In this paper, we specifically address the role of surprise in learning and memory. Although surprise has been cast as a basic emotion since Darwin's (1872) The Expression of the Emotions in Man and Animals, recently more emphasis has been placed on its cognitive aspects. One such view casts surprise as a process of “sense making” or “explanation finding”: metacognitive explanation‐based theory proposes that people's perception of surprise is a metacognitive assessment of the cognitive work done to explain a surprising outcome. Or, to put it more simply, surprise increases with the explanatory work required to resolve it. This theory predicts that some surprises should be more surprising than others because they are harder to explain. In the current paper, this theory is extended to consider the role of surprise in learning as evidenced by memorability. This theory is tested to determine how scenarios with differentially surprising outcomes impact the memorability of those outcomes. The results show that surprising outcomes (less‐known outcomes) that are more difficult to explain are recalled more accurately than less‐surprising outcomes that require little (known outcomes) or no explanation (normal).
447Scopus© Citations 24 - PublicationIntuitionistic Fuzzy Logit Model of Discrete ChoiceIn the real-world multicriteria decision making, the evaluations of the various criteria are often vague (or not crisp). The existing choice models are difficult to apply in such situations. In this paper, we introduce an intuitionistic fuzzy variant of the multinomial logit model, which helps us to suggest a decision-maker's likely choices with vague evaluations. The applicability of the proposed model is shown through a real multicriteria decision-making application.
420Scopus© Citations 1 - PublicationSystems in Language: Text Analysis of Government Reports of the Irish Industrial School System with Word EmbeddingIndustrial Memories is a digital humanities initiative to supplement close readings of a government report with new distant readings, using text analytics techniques. The Ryan Report (2009), the official report of the Commission to Inquire into Child Abuse (CICA), details the systematic abuse of thousands of children 15 from 1936 to 1999 in residential institutions run by religious orders and funded and overseen by the Irish State. Arguably, the sheer size of the Ryan Report—over 1 million words— warrants a new approach that blends close readings to witness its findings, with distant readings that help surface system-wide findings embedded in the Report. Although CICA has been lauded internationally for 20 its work, many have critiqued the narrative form of the Ryan Report, for obfuscating key findings and providing poor systemic, statistical summaries that are crucial to evaluating the political and cultural context in which the abuse took place (Keenan, 2013, Child Sexual Abuse and the Catholic Church: Gender, Power, and Organizational Culture. Oxford University Press). In this article, we concentrate on describing the distant reading methodology we adopted, using machine learning and text-analytic methods and report on what they surfaced from the 2 Report. The contribution of this work is threefold: (i) it shows how text analytics can be used to surface new patterns, summaries and results that were not apparent via close reading, (ii) it demonstrates how machine learning can be used to annotate text by using word embedding to compile domain-specific semantic lexicons for feature extraction and (iii) it demonstrates how digital humanities methods can be applied to an official state inquiry with social justice impact.
321 - PublicationAre people biased in their use of search engines?Search-engines are among the most used resources on the Internet. Google, for example, now hosts over eight billion items and returns answers to queries in a fraction of a second, thus realising some of the more far-fetched predictions envisioned by the pioneers of the World Web Web. In the present study, we assess whether people are biased in their use of a search-engine; specifically, whether they are biased in clicking on those items that are presented as being the most relevant in the search engine’s result list (i.e., those items listed at the top of the result list). To test this bias hypothesis, we simulated the Google environment systematically reversing Google’s normal relevance-ordering of the items presented to users. Our results show that people do manifest some bias, favoring items at the top of result lists, though they also sometimes seek out high-relevance items listed further down a list. Later, we discuss whether this bias arises from people’s implicit trust in a search engine, like Google, or some other effect.
3262Scopus© Citations 93