Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/11320
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dc.contributor.authorBagul, Jagruti-
dc.date.accessioned2022-10-06T08:46:31Z-
dc.date.available2022-10-06T08:46:31Z-
dc.date.issued2022-06-01-
dc.identifier.urihttp://10.1.7.192:80/jspui/handle/123456789/11320-
dc.description.abstractReal-time Conversational AI Application for Healthcare Domain's main goal is to create a real-time communication system to reduce low-pitch sounds and noise levels. We're using Nvidia Nemo SDK, Nvidia Riva, Amazon Services, and open-source platforms like RASA and Facebook Blender 2.0 chatbot. Our chatbot differs from conversational AI-based chatbots because neural networks are used in text mining consumer feedback. We can say Conversational AI applications an Intelligent Virtual Assistants(IAV), which converse like a human being. An IAV is used for computer programs that conduct a natural language via speech to text, understand the user's intents, and respond based on the organization's/business company's and healthcare patients/doctors with rules and data. We have used Bert and GPT ConvAI models for finetune and pretrained them with some datasets. Neurodegenerative disease patients need a therapist for recovery, so our conversational IAV helps them cure, and the patients do not feel lonely.en_US
dc.publisherInstitute of Technologyen_US
dc.relation.ispartofseries20MCEC02;-
dc.subjectComputer 2020en_US
dc.subjectProject Report 2020en_US
dc.subjectComputer Project Reporten_US
dc.subjectProject Reporten_US
dc.subject20MCEen_US
dc.subject20MCECen_US
dc.subject20MCEC02en_US
dc.titleReal-time Conversational AI Application for Healthcare Domainen_US
dc.typeDissertationen_US
Appears in Collections:Dissertation, CE

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