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Incorporating Uncertainty into Deep Learning for Spoken Language Assessment
2017
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
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Thanks to Cambridge English, University of Cambridge, for support and access to the BULATS data. ...
Acknowledgments This research was funded under the ALTA Institute, University of Cambridge as well as the Engineering and Physical Sciences Research Council. ...
grade and the uncertainty in the prediction. ...
doi:10.18653/v1/p17-2008
dblp:conf/acl/MalininRKG17
fatcat:naphaeh4yveybodehk6farlcky
Fuzzy Systems in AI: An Overview
[chapter]
1994
Fuzzy-Systems in Computer Science
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This paper reviews motivations for introducing fuzzy sets and fuzzy logic to knowledge representation in artificial intelligence. ...
We distinguish methods for describing natural, artificial, and abstract systems and contrast the modeling of system function with the modeling of system behavior in connection with the representation of ...
Acknowledgments I thank Jörg Gebhardt, Jochen Heinsohn, and Ramon López de Mántaras for valuable comments on an earlier version of this paper. ...
doi:10.1007/978-3-322-86825-1_12
fatcat:ossr654tufdoxba5lvuxharxii
Artificial intelligence: future impacts, challenges and recommendations on healthcare services
2020
International Journal of Community Medicine and Public Health
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In this report, we review the market impact of artificial intelligence (AI) in healthcare and future predictions. AI is a rapidly advancing technology in healthcare. ...
Interest and investment in artificial intelligence continues to grow. At the same time there exists some practical challenges that will determine the course of this market trend. ...
Prediction is beneficial in uncertainty; it allows us to make an informed decision. Any business thrives with tools that enables them to make a logical forecast and increases productivity. ...
doi:10.18203/2394-6040.ijcmph20201480
fatcat:kpyayupydbhe3d4pqubupnu36q
Neurophysiological Markers of Statistical Learning in Music and Language: Hierarchy, Entropy, and Uncertainty
2018
Brain Sciences
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SL is an interdisciplinary notion that incorporates information technology, artificial intelligence, musicology, and linguistics, as well as psychology and neuroscience. ...
This paper reviews a range of work on SL in adults and children that suggests overlapping and independent neural correlations in music and language, and that indicates disability of SL. ...
The entropy and uncertainty (i.e., summary statistics), as well as TPs, are used to understand the general predictability of sequences in domain-general SL that could cover music and language in the interdisciplinary ...
doi:10.3390/brainsci8060114
pmid:29921829
pmcid:PMC6025354
fatcat:lqhjnxdcarf4zer275iagdcb2m
Order Matters! Influences of Linear Order on Linguistic Category Learning
2020
Cognitive Science
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In two discriminative learning simulations and an artificial language learning experiment, we identify two factors that modulate linear order effects in linguistic category learning: category structure ...
and the level of abstraction in a category hierarchy. ...
We thank Harald Baayen and Petar Milin for discussion and comments.
Open Research badges This article has earned Open Data badge. ...
doi:10.1111/cogs.12910
pmid:33124103
fatcat:ooqqd3zjovaapfypla4pjfkdni
Affect Recognition for Multimodal Natural Language Processing
2020
Cognitive Computation
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Acknowledgments The guest editors are grateful to the Editor-in-Chief, Amir Hussain, and to the many reviewers who kindly agreed to serve for this special issue and submitted their insightful reviews in ...
In particular, the authors have adopted a multi-task learning framework with two tasks: initial emotion recognition and perception uncertainty prediction. ...
Computational analysis of human multimodal language is an emerging research area in natural language processing (NLP). ...
doi:10.1007/s12559-020-09738-0
fatcat:lmospfzn3barvk6fwnnk2rvw3i
Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction
2019
Journal of Economic Perspectives
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Machine learning does not represent an increase in artificial general intelligence of the kind that could substitute machines for all aspects of human cognition, ...
The majority of recent achievements in artificial intelligence are the result of advances in machine learning, a branch of computational statistics. ...
In this setting, artificial intelligence predicts how a human would translate a string of characters from one language into another. ...
doi:10.1257/jep.33.2.31
fatcat:ikcn3ztivneo5m3e6henkfkswm
COVID-19: Optimizing Business Performance through Agile Business Intelligence and Data Analytics
2020
Open Journal of Business and Management
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to survive and stay competitive during these challenging times by leveraging agile dimensions, artificial intelligence systems, and data analytics. ...
The current COVID-19 pandemic has led to a devastating socio-economic predicament, which has resulted in the temporary closure and collapse of thousands of businesses across the globe. ...
Access to data and information in real-time is a crucial requirement and determinant for an organization's agility in dealing with uncertainties. ...
doi:10.4236/ojbm.2020.85126
fatcat:mhk5v3hrwza5rniztesvtwvaiq
Towards an Intelligent Personalized Persuasive Conversational System for Human Interaction on Divining the Future Event and Assisting by Using Artificial Intelligence
2021
International Journal for Research in Applied Science and Engineering Technology
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In the next wave of insurgence, humans may endeavour self-reflection which can lead to an effortless talk and to find out if an event will fructify. ...
Artificial Intelligence Markup Language (AIML) is derived from Extensible Markup Language (XML) which is used to build up a conversational agent artificially. ...
His invaluable suggestions and practical advice helped us tremendously during our research and planning of this project. ...
doi:10.22214/ijraset.2021.35745
fatcat:zniwjz3pdra3japsblxq5ol6yq
Drug discovery with explainable artificial intelligence
[article]
2020
arXiv
pre-print
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Deep learning bears promise for drug discovery, including advanced image analysis, prediction of molecular structure and function, and automated generation of innovative chemical entities with bespoke ...
This review summarizes the most prominent algorithmic concepts of explainable artificial intelligence, and dares a forecast of the future opportunities, potential applications, and remaining challenges ...
The final prediction is obtained by aggregating the predictions of all models (e.g., as the average,ȳ), while an uncertainty estimate can be obtained from the respective predictive variance, e.g., in the ...
arXiv:2007.00523v2
fatcat:vwbm5ctaengetbsrkqjf54hoei
Using Sampling to Estimate and Improve Performance of Automated Scoring Systems with Guarantees
2022
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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Automated Scoring (AS), the natural language processing task of scoring essays and speeches in an educational testing setting, is growing in popularity and being deployed across contexts from government ...
examinations to companies providing language proficiency services. ...
The Central European Framework of Reference for Languages (CEFR) is an international standard for measuring language proficiency and assigns scores on a six-point scale from A1 (beginner) to C2 (proficient ...
doi:10.1609/aaai.v36i11.21563
fatcat:6jmfwfwmc5d3fj3igwdai6tdpe
Contextual predictability shapes signal autonomy
2018
Cognition
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Taken together, 25 these results suggest that our pragmatic faculty, and how it integrates information from the context in reducing uncertainty, plays a central role in shaping ...
will be interpreted, and the semantic 20 dimension which discriminates between meanings in context is consistent across communicative episodes), languages develop which rely heavily on the context to ...
Manipulating Contextual Predictability In our experiment, participants are first trained on an initially ambiguous artificial language, and then placed in an asymmetric communication game (Moreno & Baggio ...
doi:10.1016/j.cognition.2018.03.002
pmid:29533765
fatcat:oprlcgvmovctddnx26reyggpfi
Law As Computation in the Era of Artificial Legal Intelligence. Speaking Law to the Power of Statistics
2017
Social Science Research Network
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The resulting artificial legal intelligence may be far more successful in terms predicting the content of positive law. ...
In this article, I discuss the assumptions of law and the rule of law and confront them with those of computational systems. ...
The shift from reason to statistics, and from argumentation to simulation is the most obvious ...
doi:10.2139/ssrn.2983045
fatcat:m2vy5z3vrrdhho4givzbxrnrlq
Artificial Intelligence in Healthcare: An Overview
2020
International Journal of Engineering Research and Advanced Technology
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The use of artificial intelligence in healthcare is an emerging scientific area that aims to generate healthcare intelligence by analyzing health data. ...
This paper provides an overview of a broad range of applications of AI in healthcare. ...
Fuzzy logic deals with uncertainty in knowledge that simulates human reasoning in incomplete or fuzzy data. ...
doi:10.31695/ijerat.2020.3670
fatcat:ajx7w7l62zcnfaznzmkxlkv33a
Probabilistic machine learning and artificial intelligence
2015
Nature
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Probability theory is the mathematical language for representing and manipulating uncertainty [10], in much the same way as calculus is the language for representing and manipulating rates of change. ...
science, and artificial intelligence. ...
Probability theory is the mathematical language for representing and manipulating uncertainty [10] , in much the same way as calculus is the language for representing and manipulating rates of change. ...
doi:10.1038/nature14541
pmid:26017444
fatcat:sw42v3vzcraj3mhimxr4w2g6du
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