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A Short Review of Symbol Grounding in Robotic and Intelligent Systems

Silvia Coradeschi, Amy Loutfi, Britta Wrede
2013 Künstliche Intelligenz  
The focus is in the use of symbol grounding for robotics and intelligent system.  ...  The review covers a number of subtopics, that include, physical symbol grounding, social symbol grounding, symbol grounding for vision systems, anchoring in robotic systems, and learning symbol grounding  ...  Acknowledgements We would like to thank Tony Belpaeme, Fredrik Heintz, Sven Albrecht, Angelo Cangelosi, Paul Vogt, Katerina Pastra and Sverin Lemaignan for their helpful comments to improve the article  ... 
doi:10.1007/s13218-013-0247-2 fatcat:ghimcniy6na3fk7yqf54typjiu

Systems of natural-language-facilitated human-robot cooperation: A review [article]

Rui Liu, Xiaoli Zhang
2017 arXiv   pre-print
Natural-language-facilitated human-robot cooperation (NLC), in which natural language (NL) is used to share knowledge between a human and a robot for conducting intuitive human-robot cooperation (HRC),  ...  Currently, NLC is used in several robotic domains such as manufacturing, daily assistance and health caregiving.  ...  common sense; daily assistance common sense and caregiving common sense into the input NL data; real-time and context-aware task execution by aligning NL expressions with knowledge related to tasks, robots  ... 
arXiv:1701.08269v2 fatcat:54fstpat7rh5pbbrwbxsgwuzv4

MEDUSA: large scale automatic selection and visual assessment of PCR primer pairs

R. M. Podowski, E. L. L. Sonnhammer
2001 Bioinformatics  
The bioinformatics approaches to this problem assist researchers in advancing our understanding of the functional of human protein encoding genes.  ...  This thesis explores the hypothesis that computational methods can facilitate the identification and characterization of poorly annotated genes.  ...  In developing a method for general word sense disambiguation using unsupervised learning, Yarowsky [90] took a document classification approach to solving the problem of general term disambiguation.  ... 
doi:10.1093/bioinformatics/17.7.656 pmid:11448885 fatcat:bmepasqiznhvdabpxrnwlzqy2q

Intelligent and fuzzy systems applied to language & knowledge engineering

D. Pinto, V. Singh, David Pinto, Vivek Singh
2019 Journal of Intelligent & Fuzzy Systems  
, word sense disambiguation, reputation analysis, etc.  ...  Experiments for 7 classifiers and 4 methods of linear regression on Russian Readability corpus demonstrated that ranking textbooks for native speakers is a much more difficult task than ranking examination  ...  Sidorov et al. in their paper "Human interaction with shopping assistant robot in natural language" present a language-independent spoken dialog management module integrated into a human-robot interaction  ... 
doi:10.3233/jifs-179006 fatcat:hs76dvlsfnbpngmglwuq6aemda

Interactive sense feedback for difficult queries

Alexander Kotov, ChengXiang Zhai
2011 Proceedings of the 20th ACM international conference on Information and knowledge management - CIKM '11  
In this work, we propose to involve a user in the process of disambiguation through interactive sense feedback and study the potential effectiveness of this novel feedback strategy.  ...  We evaluated the effectiveness of the proposed methods for sense identification and presentation through simulation experiments and user studies, which both indicate that sense feedback strategy is a promising  ...  In this work, we propose interactive sense feedback (ISF), a new method for interactive query disambiguation and reformulation, which, unlike the previously proposed methods for interactive relevance feedback  ... 
doi:10.1145/2063576.2063605 dblp:conf/cikm/KotovZ11 fatcat:uhqitg7os5e6dhrvkwe7ia6jem

Natural Language Processing: State of The Art, Current Trends and Challenges [article]

Diksha Khurana, Aditya Koli, Kiran Khatter, Sukhdev Singh
2017 arXiv   pre-print
Natural language processing (NLP) has recently gained much attention for representing and analysing human language computationally.  ...  It has spread its applications in various fields such as machine translation, email spam detection, information extraction, summarization, medical, and question answering etc.  ...  Word Sense Disambiguation (Word sense disambiguation is the task of understanding the correct sense of a word in context.  ... 
arXiv:1708.05148v1 fatcat:7dvsgmaslvddhdiy3udohgudky

Recent Advances in Information Technology

Fei Yu, Chin-Chen Chang, Yiqin Lu, Jian Shu, Yan Gao, Guangxue Yue, Zuo Chen
2014 The Scientific World Journal  
Wang et al. proposes a novel approach to word sense disambiguation based on topical and semantic association.  ...  The key visualization algorithm and technology of the system are mainly discussed. The paper entitled "A novel approach to word sense disambiguation based on topical and semantic association" by X.  ...  We wish to express our deepest thanks to the program committee members for their help in selecting papers for this issue and especially the referees of the extended versions of the selected papers for  ... 
doi:10.1155/2014/746479 pmid:25110742 pmcid:PMC4119702 fatcat:f3yq2agpevcvdbxe44umitvxa4

Selected Ph.D. Thesis Abstracts

Xin Li
2017 The IEEE intelligent informatics bulletin  
For highly non-linear robotic systems, such as in presence of contacts, the use of analytical system identification techniques can be challenging and time-consuming, or even intractable.  ...  A key challenge, in this regard, entails the need for precise identification and disambiguation of entities across documents for extraction of attributes/relations and their proper representation in knowledge  ... 
dblp:journals/cib/Li17 fatcat:3rekqnvlozdwjcyt4hs3uyipom

Prepositions in Applications: A Survey and Introduction to the Special Issue

Timothy Baldwin, Valia Kordoni, Aline Villavicencio
2009 Computational Linguistics  
and the word sense disambiguation of content words.  ...  In addition to standalone word sense disambiguation tasks, however, there needs to be more research on the interaction of preposition semantics with other semantic tasks, such as semantic role labeling  ... 
doi:10.1162/coli.2009.35.2.119 fatcat:kxejjmz42vasbmnlgksnbyc6iy

Meeting them halfway: Altering language conventions to facilitate human-robot interaction

Lize Alberts
2019 Stellenbosch Papers in Linguistics Plus  
This article considers the remaining hindrances for natural language processing technologies in achieving open and natural (human-like) interaction between humans and computers.  ...  Although artificially intelligent (AI) systems have been making great strides in this field, particularly with the development of deep learning architectures that carry surface-level statistical methods  ...  may prove useful in the case of human-robot interaction as well.  ... 
doi:10.5842/56-0-799 fatcat:vftajhzhc5aotlhahdxn3yrqtq

The CLSA Model: A Novel Framework for Concept-Level Sentiment Analysis [chapter]

Erik Cambria, Soujanya Poria, Federica Bisio, Rajiv Bajpai, Iti Chaturvedi
2015 Lecture Notes in Computer Science  
Such algorithms are very good at retrieving texts, splitting them into parts, checking the spelling, and counting their words.  ...  Contrary or complementary attitudes toward the same topic or multiple topics can be present across the span of a review.  ...  The approach used NLP techniques to extract features of interest from textual data retrieved from a microblogging platform in real-time and, hence, to generate appropriate executable code for the robot  ... 
doi:10.1007/978-3-319-18117-2_1 fatcat:zlu3xwbijjcbxhq3tngtxqljz4

Computational modeling of phonetic and lexical learning in early language acquisition: Existing models and future directions

Okko Räsänen
2012 Speech Communication  
This work reviews a number of existing computational studies concentrated on the question of how spoken language can be learned from continuous speech in the absence of linguistically or phonetically motivated  ...  Specifically, the focus is on how phonetic categories and word-like units can be acquired purely on the basis of the statistical structure of speech signals, possibly aided by some articulatory or visual  ...  Moore, and the two anonymous reviewers for their invaluable comments on the manuscript. COMPUTATIONAL MODELING OF EARLY LANGUAGE ACQUISITION 54  ... 
doi:10.1016/j.specom.2012.05.001 fatcat:lxqfltnne5gt5mibfrqj2vzmhi

Enabling Multimodal Human–Robot Interaction for the Karlsruhe Humanoid Robot

Rainer Stiefelhagen, Hazim Kemal Ekenel, Christian Fugen, Petra Gieselmann, Hartwig Holzapfel, Florian Kraft, Kai Nickel, Michael Voit, Alex Waibel
2007 IEEE Transactions on robotics  
In this paper, we present our work in building technologies for natural multimodal human-robot interaction.  ...  The work and the components presented here constitute the core building blocks for audiovisual perception of humans and multimodal human-robot interaction used for the humanoid robot developed within the  ...  ACKNOWLEDGMENT The authors would like to thank all colleagues in the Interactive Systems Laboratories and in the SFB 588 for their support.  ... 
doi:10.1109/tro.2007.907484 fatcat:mstaffju6fdu5abbbvrkh56jkm

Is it possible not to cheat on the Turing Test_Exploring the potential and challenges for true natural language 'understanding' by computers [article]

Lize Alberts
2022 arXiv   pre-print
The increasing sophistication of NLP models has renewed optimism regarding machines achieving a full human-like command of natural language.  ...  In this paper, I unite all of these perspectives -- the philosophical, cognitive-linguistic, and technical -- to unpack the challenges involved in approaching true (human-like) language understanding.  ...  Acknowledgments This work is a shortened version of my master's by research thesis in philosophy. I would like to thank my supervisor, Dr. J.P. Smit, for his support and brilliance, as well as Dr. G.  ... 
arXiv:2206.14672v3 fatcat:tsz5l5igb5ddtdzyreisitqpru

Self-Supervised Euphemism Detection and Identification for Content Moderation [article]

Wanzheng Zhu, Hongyu Gong, Rohan Bansal, Zachary Weinberg, Nicolas Christin, Giulia Fanti, Suma Bhat
2021 arXiv   pre-print
This paper will demonstrate unsupervised algorithms that, by analyzing words in their sentence-level context, can both detect words being used euphemistically, and identify the secret meaning of each word  ...  Compared to the existing state of the art, which uses context-free word embeddings, our algorithm for detecting euphemisms achieves 30-400% higher detection accuracies of unlabeled euphemisms in a text  ...  In a more general sense, the task of euphemism identification is also related to sense discovery of unknown words [60] , [61] and word sense disambiguation [62] - [65] .  ... 
arXiv:2103.16808v1 fatcat:z44viumb25bxdmdyr66gfoxipu
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