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dc.contributor.authorPanesar, Kulvinder
dc.date.accessioned2020-10-05T14:14:10Z
dc.date.accessioned2020-10-15T14:46:33Z
dc.date.available2020-10-05T14:14:10Z
dc.date.available2020-10-15T14:46:33Z
dc.date.issued2020-05
dc.identifier.citationPanesar K (2020) Conversational artificial intelligence – demystifying statistical vs linguistic NLP solutions. Journal of Computer-Assisted Linguistic Research. 4: 47-79en_US
dc.identifier.urihttp://hdl.handle.net/10454/18121
dc.descriptionyesen_US
dc.description.abstractThis paper aims to demystify the hype and attention on chatbots and its association with conversational artificial intelligence. Both are slowly emerging as a real presence in our lives from the impressive technological developments in machine learning, deep learning and natural language understanding solutions. However, what is under the hood, and how far and to what extent can chatbots/conversational artificial intelligence solutions work – is our question. Natural language is the most easily understood knowledge representation for people, but certainly not the best for computers because of its inherent ambiguous, complex and dynamic nature. We will critique the knowledge representation of heavy statistical chatbot solutions against linguistics alternatives. In order to react intelligently to the user, natural language solutions must critically consider other factors such as context, memory, intelligent understanding, previous experience, and personalized knowledge of the user. We will delve into the spectrum of conversational interfaces and focus on a strong artificial intelligence concept. This is explored via a text based conversational software agents with a deep strategic role to hold a conversation and enable the mechanisms need to plan, and to decide what to do next, and manage the dialogue to achieve a goal. To demonstrate this, a deep linguistically aware and knowledge aware text based conversational agent (LING-CSA) presents a proof-of-concept of a non-statistical conversational AI solution.en_US
dc.language.isoenen_US
dc.publisherUniversitat Politécnica de Valéncia
dc.rights© 2020 The Author. Published by Universitat Politecnica de Valencia. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.subjectConversational artificial intelligenceen_US
dc.subjectKnowledge representationen_US
dc.subjectMachine/deep learningen_US
dc.subjectNatural language understandingen_US
dc.subjectNatural language processingen_US
dc.subjectRole and reference grammaren_US
dc.titleConversational artificial intelligence - demystifying statistical vs linguistic NLP solutionsen_US
dc.status.refereedyesen_US
dc.date.Accepted2020-04-05
dc.typeArticleen_US
dc.type.versionPublished versionen_US
dc.identifier.doihttps://doi.org/10.4995/jclr.2020.12932
dc.date.updated2020-10-05T13:14:18Z
refterms.dateFOA2020-10-15T14:47:21Z


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