Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)

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MARGEN: Marathi Question Answering Generative Conversation Model

Authors
Satish V. Bhalshankar1, *, Ratnadeep R. Deshmukh1
1Department of Computer Science and IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, MH, India
*Corresponding author. Email: sbhalshankar.mgmtsci@bamu.ac.in
Corresponding Author
Satish V. Bhalshankar
Available Online 1 May 2023.
DOI
10.2991/978-94-6463-136-4_46How to use a DOI?
Keywords
Generative Chatbot; GPT; IndicBART; AI; NLP; RNN; LSTM; Dataset
Abstract

The conversational system aka chatbot market capture was worth USD 526 million in 2021 around the world. The innovations created such as Machine learning, Deep learning, Natural Language Processing (NLP), and Big data analytics have given a modern speed-quickening fuel to Artificial Intelligence. Well, a generative chatbot could be an exceptionally effective and shrewd conversational system as distant as its learning component is concerned. They can be trained from scratch like a newborn child by using Deep Learning techniques. GPT-1,2,3 is well known for English Language NLP tasks whereas IndicBART is also moving ahead for 11 Indian Languages for the NLU tasks. With the DL techniques like RNN, LSTM, and SGD, we conducted an in-depth survey of recent deep learning conversational models available on open-source portals, examining over 25 deep learning models for conversational systems before proposing our model. "MARGEN" is a proposed model which means the user can get the system's reply with proper generative answers for the query in Marathi text and/or audio speech formats.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
Series
Advances in Computer Science Research
Publication Date
1 May 2023
ISBN
978-94-6463-136-4
ISSN
2352-538X
DOI
10.2991/978-94-6463-136-4_46How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Satish V. Bhalshankar
AU  - Ratnadeep R. Deshmukh
PY  - 2023
DA  - 2023/05/01
TI  - MARGEN: Marathi Question Answering Generative Conversation Model
BT  - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
PB  - Atlantis Press
SP  - 527
EP  - 556
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-136-4_46
DO  - 10.2991/978-94-6463-136-4_46
ID  - Bhalshankar2023
ER  -