Please use this identifier to cite or link to this item:
Title: Domain Specific Conversational Intelligence: Voice Based E-Channeling System
Authors: Weerathunga, W. A. H
Lokugamage, G. N
Hariharan, H
Yahampath, A. D. N. H
Kasthurirathna, D
Keywords: Domain Specific
Conversational Intelligence
Voice Based
E-Channeling System
Issue Date: 10-Dec-2020
Citation: W. A. H. Weerathunga, G. N. Lokugamage, H. V, A. D. N. H. Yahampath and D. Kasthurirathna, "Domain Specific Conversational Intelligence: Voice Based E-Channeling System," 2020 2nd International Conference on Advancements in Computing (ICAC), 2020, pp. 494-499, doi: 10.1109/ICAC51239.2020.9357308.
Series/Report no.: 2020 2nd International Conference on Advancements in Computing (ICAC);Volume 1 Pages 494-499
Abstract: In this research the application of Automatic Speech Recognition, Natural Language Understanding, Neural Networks and Text To Speech Conversion is investigated to create a domain specific end to end voice based E-Channeling system. The novel idea in this research can be extended to any other domain(e.g.: Taxi Application) and build a conversational intelligence system. This system enables the user to avoid the shortcomings in the traditional doctor appointment channeling procedures. The system also have the ability to predict the doctor specialization according to the symptoms of the patient and can give emergency health tips by using the powerful Neural Network module. Domain-specific speech recognition model is created according to Sri Lankan accents and handles the context-specific to this domain(94% accuracy). Extracting the entities, handling e-channeling functions and selecting the most suitable API is done by the RASA backend. Neural Network will give the first aid and doctor specialization recommendations according to user input with a validation accuracy of 90%. Speech synthesis model will output the response in user preferred language(Sinhala, English or Tamil).
ISBN: 978-1-7281-8412-8
Appears in Collections:Research Papers - Dept of Computer Science and Software Engineering
Research Papers - IEEE
Research Papers - SLIIT Staff Publications

Files in This Item:
File Description SizeFormat 
  Until 2050-12-31
484.12 kBAdobe PDFView/Open Request a copy

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.