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dc.contributor.authorLiebman, David
dc.date.accessioned2020-12-18T18:15:09Z
dc.date.available2020-12-18T18:15:09Z
dc.date.issued2020-12
dc.identifier.urihttp://hdl.handle.net/20.500.12648/1594
dc.description.abstractThe goal in this thesis is to create a chatbot, a computer program that can respond verbally to a human in the course of simple day-to-day conversations. A deep learning neural network model called the Transformer is used to develop the chatbot. A full description of a Transformer is provided. The use of a few different Transformer-based Natural Language Processing models to develop the chatbot, including Generative Pre-Training 2 (GPT2), are shown. For comparison a Gated Recurrent Unit (GRU) based model is included. Each of these are explained below. The chatbot code is installed on a small device such as the Raspberry Pi with speech recognition and speech-to-text software. In this way a device that can carry out a verbal conversation with a human might be created. For the GRU-based model a Raspberry Pi 3B with 1GB RAM can be used. A Raspberry Pi 4B with 4GB of RAM is needed to run a chatbot with the GPT2.en_US
dc.language.isoen_USen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectResearch Subject Categories::TECHNOLOGY::Information technology::Computer scienceen_US
dc.subjectNatural language processingen_US
dc.subjectHuman-computer interactionen_US
dc.subjectRaspberry Pi (Computer)en_US
dc.subjectChatboten_US
dc.titleA generative chatbot with natural language processingen_US
dc.typeThesisen_US
dc.description.versionNAen_US
refterms.dateFOA2020-12-18T18:15:10Z
dc.description.institutionSUNY College at New Paltzen_US
dc.description.departmentComputer Scienceen_US
dc.description.degreelevelMSen_US
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Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International