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2024

Journal Article Exploring the Efficacy of Large Language Models in Summarizing Mental Health Counseling Sessions: Benchmark Study
Prottay Kumar Adhikary, Aseem Srivastava ,Shivani Kumar, Salam Michael Singh, Puneet Manuja, Jini K Gopinath, Vijay Krishnan, Swati Kedia Gupta, Koushik Sinha Deb, Tanmoy Chakraborty
JMIR Ment Health | February, 2024
@article{adhikary2024exploring, title={Exploring the Efficacy of Large Language Models in Summarizing Mental Health Counseling Sessions: Benchmark Study}, author={Adhikary, Prottay Kumar and Srivastava, Aseem and Kumar, Shivani and Singh, Salam Michael and Manuja, Puneet and Gopinath, Jini K and Krishnan, Vijay and Gupta, Swati Kedia and Deb, Koushik Sinha and Chakraborty, Tanmoy}, journal={JMIR Mental Health}, volume={11}, pages={e57306}, year={2024}, publisher={JMIR Publications Toronto, Canada} }

2023

Conference Paper TRAVID: An End-to-End Video Translation Framework
Prottay Kumar Adhikary, Bandaru Sugandhi, Subhojit Ghimire, Santanu Pal, Partha Pakray
IJCNLP-AACL 2023, Bali, Indonesia | November, 2023
@InProceedings{adhikary-EtAl:2023:ijcnlp, author = {Adhikary, Prottay Kumar and Sugandhi, Bandaru and Ghimire, Subhojit and Pal, Santanu and Pakray, Partha}, title = {TRAVID: An End-to-End Video Translation Framework}, booktitle = {System Demonstrations}, month = {November}, year = {2023}, address = {Bali, Indonesia}, publisher = {Asian Federation of Natural Language Processing}, pages = {1--9} }

Conference Paper CNLP-NITS at SemEval-2023 Task 10: Online sexism prediction, PREDHATE!
Advaitha Vetagiri, Prottay Kumar Adhikary, Partha Pakray, Amitava Das
The 17th International Workshop on Semantic Evaluation (SemEval-2023) | July, 2023
@inproceedings{vetagiri-etal-2023-cnlp, title = "{CNLP}-{NITS} at {S}em{E}val-2023 Task 10: Online sexism prediction, {PREDHATE}!", author = "Vetagiri, Advaitha and Adhikary, Prottay and Pakray, Partha and Das, Amitava", booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)", month = jul, year = "2023", address = "Toronto, Canada", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2023.semeval-1.113", doi = "10.18653/v1/2023.semeval-1.113", pages = "815--822", abstract = "Online sexism is a rising issue that threatens women{'}s safety, fosters hostile situations, and upholds social inequities. We describe a task SemEval-2023 Task 10 for creating English-language models that can precisely identify and categorize sexist content on internet forums and social platforms like Gab and Reddit as well to provide an explainability in order to address this problem. The problem is divided into three hierarchically organized subtasks: binary sexism detection, sexism by category, and sexism by fine-grained vector. The dataset consists of 20,000 labelled entries. For Task A, pertained models like Convolutional Neural Network (CNN) and Bidirectional Long Short-Term Memory (BiLSTM), which is called CNN-BiLSTM and Generative Pretrained Transformer 2 (GPT-2) models were used, as well as the GPT-2 model for Task B and C, and have provided experimental configurations. According to our findings, the GPT-2 model performs better than the CNN-BiLSTM model for Task A, while GPT-2 is highly accurate for Tasks B and C on the training, validation and testing splits of the training data provided in the task. Our proposed models allow researchers to create more precise and understandable models for identifying and categorizing sexist content in online forums, thereby empowering users and moderators.", }

Conference Paper Leveraging GPT-2 for automated classification of online sexist content
Advaitha Vetagiri, Prottay Kumar Adhikary, Partha Pakray, Amitava Das
Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2023)| May, 2023
@article{vetagiri2023leveraging, title={Leveraging GPT-2 for automated classification of online sexist content}, author={Vetagiri, Advaitha and Adhikary, Prottay Kumar and Pakray, Partha and Das, Amitava}, year={2023} }

Journal Dzongkha Handwritten Digit Recognition using Machine Learning Techniques
Prottay Kumar Adhikary, Pankaj Dadure, Pradipta Saha, Partha Pakray
Procedia Computer Science | January, 2023
@article{ADHIKARY20232350, title = {Dzongkha Handwritten Digit Recognition using Machine Learning Techniques}, journal = {Procedia Computer Science}, volume = {218}, pages = {2350-2358}, year = {2023}, note = {International Conference on Machine Learning and Data Engineering}, issn = {1877-0509}, doi = {https://doi.org/10.1016/j.procs.2023.01.210}, url = {https://www.sciencedirect.com/science/article/pii/S1877050923002107}, author = {Prottay Kumar Adhikary and Pankaj Dadure and Pradipta Saha and Tawmo and Partha Pakray}, keywords = {Dzongkha Language, Character Recognition, Digit Recognition, Handwritten Characters, Machine Learning}, abstract = {Handwritten digit recognition has recently gained importance, attracting many researchers due to its use in various machine learning and computer vision applications. As technology and science progressing, there is a need for a system to recognize the handwritten script in several real-time applications to reduce human effort. There a lot of work has been done on the recognition and generation of handwritten digits of high-resource languages such as English. However, insufficient work has been done on Dzongkha digits recognition, as Dzongkha digits are low-resource and more complex than English patterns. This paper aims to perform handwritten character recognition of Dzongkha digit using several machine learning techniques. The unavailability of the Dzongkha handwritten digit dataset is the prime motivation behind this work. To facilitates the recognition of Dzongkha handwritten digit, we have collected the data of Dzongkha handwritten digit from indigenous and non-indigenous people of Bhutan and provided the dataset for further research. Moreover, we have used several machine algorithms, including a support vector machine, K-nearest neighbor, and decision tree. Among these algorithms, the support vector machine classification algorithm has achieved a remarkable result with an accuracy of 98.29%.} }

2022

Journal Investigation of negation effect for En-As machine translation
SR Laskar, A Gogoi, S Dutta, Prottay Kumar Adhikary, P Nath, Partha Pakray, Sivaji Bandyopadhyay
Sādhanā | November, 2022
@Article{Laskar2022, author={Laskar, Sahinur Rahman and Gogoi, Abinash and Dutta, Samudranil and Adhikary, Prottay Kumar and Nath, Prachurya and Pakray, Partha and Bandyopadhyay, Sivaji}, title={Investigation of negation effect for English--Assamese machine translation}, journal={S{\={a}}dhan{\={a}}}, year={2022}, month={Nov}, day={14}, volume={47}, number={4}, pages={238}, abstract={Computational linguistics deals with the computational modelling of natural languages, in which machine translation is a popular task. The aim of machine translation is to automatically translate one natural language into another, which minimizes the linguistic barrier of different linguistic backgrounds. The data-driven approach of machine translation, namely, neural machine translation achieves state-of-the-art results on different language pairs, however it needs a sufficient amount of parallel training data to attain reasonable translation performance. In this work, we have explored different machine translation models on a low-resource English--Assamese language pair and investigated different sources of errors, particularly due to negation in English-to-Assamese and Assamese-to-English translation. Negation is a universal, essential feature of human language that has a substantial impact on the semantics of a statement. Moreover, a rule-based approach is proposed in the data preprocessing step which handles modal-verb negation problem that shows significant improvement in translation performance in terms of automatic and manual evaluation scores.}, issn={0973-7677}, doi={10.1007/s12046-022-01965-5}, url={https://doi.org/10.1007/s12046-022-01965-5} }

Conference Paper Image Caption Generation for Low-Resource Assamese Language
Prachurya Nath, Prottay Kumar Adhikary, Pankaj Dadure, Partha Pakray, Riyanka Manna, Sivaji Bandyopadhyay
Conference on Computational Linguistics and Speech Processing (ROCLING), Taipei, Taiwan | November, 2022
@inproceedings{nath-etal-2022-image, title = "Image Caption Generation for Low-Resource {A}ssamese Language", author = "Nath, Prachurya and Adhikary, Prottay Kumar and Dadure, Pankaj and Pakray, Partha and Manna, Riyanka and Bandyopadhyay, Sivaji", booktitle = "Proceedings of the 34th Conference on Computational Linguistics and Speech Processing (ROCLING 2022)", month = nov, year = "2022", address = "Taipei, Taiwan", publisher = "The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)", url = "https://aclanthology.org/2022.rocling-1.33", pages = "263--272", abstract = "Image captioning is a prominent Artificial Intelligence (AI) research area that deals with visual recognition and a linguistic description of the image. It is an interdisciplinary field concerning how computers can see and understand digital images{\&} videos, and describe them in a language known to humans. Constructing a meaningful sentence needs both structural and semantic information of the language. This paper highlights the contribution of image caption generation for the Assamese language. The unavailability of an image caption generation system for the Assamese language is an open problem for AI-NLP researchers, and it{'}s just an early stage of the research. To achieve our defined objective, we have used the encoder-decoder framework, which combines the Convolutional Neural Networks and the Recurrent Neural Networks. The experiment has been tested on Flickr30k and Coco Captions dataset, which have been originally present in the English language. We have translated these datasets into Assamese language using the state-of-the-art Machine Translation (MT) system for our designed work.", }

Book Chapter Ontology-based healthcare hierarchy towards chatbot
Prottay Kumar Adhikary, Riyanka Manna, Sahinur Rahman Laskar, Partha Pakray
4th International Conference, CICBA 2022, Silchar, India | July, 2022
@InProceedings{10.1007/978-3-031-10766-5_26, author="Adhikary, Prottay Kumar and Manna, Riyanka and Laskar, Sahinur Rahman and Pakray, Partha", editor="Mukhopadhyay, Somnath and Sarkar, Sunita and Dutta, Paramartha and Mandal, Jyotsna Kumar and Roy, Sudipta", title="Ontology-Based Healthcare Hierarchy Towards Chatbot", booktitle="Computational Intelligence in Communications and Business Analytics", year="2022", publisher="Springer International Publishing", address="Cham", pages="326--335", abstract="Ontology refers to relationship-based hierarchical descriptions of concepts within a particular domain. Ontology, in the field of medicine, describes the concepts of medical terminologies and the relation between them, thus, enabling the sharing of medical knowledge. This paper aims to develop an ontology-based healthcare hierarchy and point out the research scope towards the chatbot application. The research scope includes the integration of the ontology-based healthcare hierarchy in the chatbot application by the establishment of relationships among individuals and real-world entities.", isbn="978-3-031-10766-5" }

Book Chapter An Empirical Analysis on Abstractive Text Summarization
Tawmo, Prottay Kumar Adhikary, Pankaj Dadure & Partha Pakray
4th International Conference, CICBA 2022, Silchar, India | July, 2022
@InProceedings{10.1007/978-3-031-10766-5_22, author="Tawmo and Adhikary, Prottay Kumar and Dadure, Pankaj and Pakray, Partha", editor="Mukhopadhyay, Somnath and Sarkar, Sunita and Dutta, Paramartha and Mandal, Jyotsna Kumar and Roy, Sudipta", title="An Empirical Analysis on Abstractive Text Summarization", booktitle="Computational Intelligence in Communications and Business Analytics", year="2022", publisher="Springer International Publishing", address="Cham", pages="280--287", abstract="With the massive growth of blogs, news stories, and reports, extracting useful information from such a large quantity of textual documents has become a difficult task. Automatic text summarization is an excellent approach for summarising these documents. Text summarization aims to condense large documents into concise summaries while preserving essential information and meaning. A variety of fascinating summarising models have been developed to achieve state-of-the-art performance in terms of fluency, human readability, and semantically meaningful summaries. In this paper, we have investigated the OpenNMT tool for task text summarization. The OpenNMT is the encoder-decoder-based neural machine translation model which has been fine-tuned for the task of abstractive text summarization. The proposed OpenNMT based text summarization approach has been tested on freely available dataset such as CNNDM {\&} MSMO dataset and depicts their proficiency in terms of ROUGE and BLEU score.", isbn="978-3-031-10766-5" }

Dataset Dzongkha Handwritten Digit Dataset
Tawmo, Prottay Kumar Adhikary Pankaj Dadure, Partha Pakray
IAPR-TC11: Association for Pattern Recognition Technical Committee Number 11 | February, 2022
@dataset{tawmo_2022_6271560, author = {Tawmo and Prottay Kumar Adhikary and Pankaj Dadure and Partha Pakray}, title = {Dzongkha Handwritten Digit Dataset}, month = feb, year = 2022, publisher = {Zenodo}, version = {1.0.0}, doi = {10.5281/zenodo.6271560}, url = {https://doi.org/10.5281/zenodo.6271560} }

2021

Conference Paper Neural Machine Translation for Tamil–Telugu Pair
Sahinur Rahman Laskar, Bishwaraj Paul, Prottay Kumar Adhikary, Partha Pakray, Sivaji Bandyopadhyay
Proceedings of the Sixth Conference on Machine Translation, EMNLP, WMT (Online) | November, 2021
@inproceedings{laskar-etal-2021-neural, title = "Neural Machine Translation for {T}amil{--}{T}elugu Pair", author = "Laskar, Sahinur Rahman and Paul, Bishwaraj and Adhikary, Prottay Kumar and Pakray, Partha and Bandyopadhyay, Sivaji", booktitle = "Proceedings of the Sixth Conference on Machine Translation", month = nov, year = "2021", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2021.wmt-1.29", pages = "284--287", abstract = "The neural machine translation approach has gained popularity in machine translation because of its context analysing ability and its handling of long-term dependency issues. We have participated in the WMT21 shared task of similar language translation on a Tamil-Telugu pair with the team name: CNLP-NITS. In this task, we utilized monolingual data via pre-train word embeddings in transformer model based neural machine translation to tackle the limitation of parallel corpus. Our model has achieved a bilingual evaluation understudy (BLEU) score of 4.05, rank-based intuitive bilingual evaluation score (RIBES) score of 24.80 and translation edit rate (TER) score of 97.24 for both Tamil-to-Telugu and Telugu-to-Tamil translations respectively.", }

Research

LCS2, IIT Delhi
Research Assistant (Onsite)   |  November 2023 - December 2023
  • Project: AI for Mental Health
  • Played a role in developing LLMs to enhance mental health counseling and address key issues within the field. Major contributions include identifying dialogue acts and summarizing mental health counseling conversations, with further work extending to aspect-based summarization of counseling components.
  • Skills: Large Language Models, Dialouge Summerization, Speaker Profiling.

CSTAR, IIIT Hyderabad
Machine Leaning Intern (Onsite)   |  August 2023 - December 2023
  • Project: Engaged in pioneering research on Quantization for Large Language Models as an Intern at Center for Security, Theory and Algorithmic Research
  • Reviewed literature related to Large Language Model quantization, with a particular focus on reparameterization-based Parameter-Efficient Fine-Tuning (PEFT) techniques. Implemented these techniques with real-world large language models (LoRA, QLoRA, AdaLoRA) and conducted research to discover new methods for enhancing compression efficiency.
  • Skills: Large Language Models, Transformers, PEFT

National Institute of Technology Silchar
Summer Research Intern (Onsite)   |  June 2022 - July 2022
  • Project: Translated English video into Hindi, Bengali, Telugu, and Nepali with lip synchronization.
  • Ensured accurate lip movements for seamless viewing across languages. Aims to bridge linguistic barriers and enhance content accessibility for diverse audiences.
  • Skills: Speech & Video Processing, Transfer Learning, Machine Translation

National Institute of Technology Silchar
Winter Research Intern (Onsite)   |  December 2021 - February 2022
  • Project: Explore machine translation for low-resource English–Assamese language pair.
  • Examined impact of negation in both English-to-Assamese and Assamese-to-English translation & investigated various sources of errors related to negation. Proposed rule-based approach in data preprocessing to handle modal-verb negation problem & achieved significant improvements in translation through scoring methods.
  • Skills: NLTK, Keras, Data Analytics, Scikit-Learn, TensorFlow, Python

Indian Institute of Technology, Guwahati
Summer Research Intern (Onsite)   |  July 2021 - September 2021
  • Project: Hate speech detection in code-mixed Assamese and Bengali YouTube comments
  • Collected dataset of code-mixed AS-BN comments & Applied data preprocessing techniques
  • Developed robust hate speech detection model using ML and NLP
  • Skills: NLTK, Keras, Scikit-Learn, TensorFlow, Python


Part-Time

Greenline Books
Web Developer (Remote)   |  August 2023 - Resumed
  • Position: Website Designing, Development & Database Maintencence
  • Created user-centric website aligning with brand identity, using Wix expertise to integrate multimedia and optimize engagement. Collaborating across teams, transformed concepts into captivating, responsive sites, staying updated on trends to deliver cutting-edge solutions that enhance online presence and user experiences
  • Skills: HTML5/CSS/JS, Wix Editor, MySQL

Level Innovations Pvt Ltd.
NLP Tutor (Remote)   |  September 2022 - Jan 2023
  • Position: Academic tutor and research assistant at Levelapp in deep learning field.
  • Provided guidance and comprehensive tutoring to enhance students’ understanding. Contributed to research projects by conducting in-depth analyses and assisting in data collection and experimentation
  • Skills: Advanced NLP, Deep Learning, PyTorch, BERT (Language Model)


Leadership

Gymkhana Union Body
International Student Representitive  |  March 2022 – June 2023
  • Advocated for the interests and concerns of international students as an International Student Representative at NIT Silchar, acting as a liaison between international students and the larger student community.
  • Organized events and activities to promote cultural exchange and integration between international and domestic students, fostering a supportive and inclusive environment.
  • Addressed and resolved various challenges faced by international students, collaborating with the university administration and faculty to ensure their overall well-being and academic success at NIT Silchar.

Notre Dame English Club
Vice President of Archive & Documentation   |  January 2018 - Jan 2023
  • Played a pivotal role in preserving and showcasing the club's historical records and literary works, enhancing its online presence.
  • Demonstrated proficiency in managing digital content and fostering a creative and literary environment.
  • Skills: Web Development, Web Content Writing, Digital Archiving


Volunteer

  • Designed Website for MIP Lab, NITS in 2023  
  • Web Developer at Indic MT Task, EMNLP 2023  
  • Program Committee Member and Reviewer at AIC 2023  
  • Program Committee Member and reviewer at PCCDA 2023 
  • Program Committee Member and reviewer at AIC 2022  
  • Program Committee Member and reviewer at ICCIS 2022  
  • Task Coordinator and Web Developer at TextSumEval 2022  
https://github.com/proadhikary/floodd
Floodd: Unraveling India's Flood Odds
 Python, Steamlit, Folium
May 2024
Floodd provides a comprehensive analysis of flood events, utilizing a range of visualizations to explore patterns, trends, and impacts based on geographical data, temporal factors, and causal information. It is designed to aid researchers, policymakers, and the public in understanding the dynamics of floods and facilitating data-driven decision-making in disaster management and mitigation strategies.
https://github.com/proadhikary/MenstBot
MenstBot: A Menstrual Health Chatbot
 Python, Langchain, Chainlit, FAISS
March 2024
MenstBot is a menstrual health chatbot based on Llama2, designed to provide information and support regarding menstruation-related queries.
https://github.com/proadhikary/TRAVID
TRAVID: Translate Videos Online
 Python, Flask, Firebase
March 2023
TRAVID is a small-scale Face-to-Face Video Translator project that lets users translate a Tshort-duration video in one language to a selected language while maintaining the lip synchronisation, as well as an attempt at voice-cloning.
https://comp-mt.streamlit.app/
COMP-MT: All-in-one Machine Translation Evaluation System
 Python, Streamlit
January 2023
COMPMT is an all-in-one MT Evaluation System designed with Streamlit, enabling users to efficiently assess their test files against gold files for comprehensive machine translation evaluation.
https://github.com/proadhikary/predhate
PredHate: Detect Sexism Online
 Python, Flask
October 2022
A flask webapp, which can detect sexism online, and provided few features like to check the history and can classify multiple text at a time.
https://github.com/CNLP-Summarization/Saransa
Saransa: An Summerization & Knowlage Graph Generation
 Python, Flask, SQL
April 2022
Saransa is a Flask-based project utilizing a pretrained BERT model to offer a powerful Summarization & Knowledge Graph Generation Tool.
Botica: Ontology Based Healthcare ChatBot
 RASA, Python
June 2021
Botica is an RASA-based Ontology-Based Healthcare ChatBot, offering a first aid help system to provide immediate medical assistance and guidance.
https://github.com/proadhikary/Beeth
Beeth: A Music Player for the Hearing Impaired
 C Language
September 2020
A music player catering to the hearing impaired, offering enhanced accessibility features for a tailored musical experience for 'Feature Phones'.
https://cse23.xyz/
⭐ CSE’23: A Web-based Distance Learning Program
 HTML, CS, JS
March 2020
CSE’23 provides information and resources for the students of Computer Science and Engineering. The website contains study materials, previous exams papers, assignments and many more. It a useful platform for those who want to learn more about computer science and engineering