no code implementations • SemEval (NAACL) 2022 • Shubham Barnwal, Ritesh Kumar, Rajendra Pamula
However, with this much contribution, it also increases systematic inequality and discrimination offline is replicated in online spaces in the form of MEMEs.
no code implementations • ACL (CASE) 2021 • Ali Hürriyetoğlu, Osman Mutlu, Erdem Yörük, Farhana Ferdousi Liza, Ritesh Kumar, Shyam Ratan
Task 1, which is the focus of this report, is on multilingual protest news detection and comprises four subtasks that are document classification (subtask 1), sentence classification (subtask 2), event sentence coreference identification (subtask 3), and event extraction (subtask 4).
no code implementations • LTEDI (ACL) 2022 • Vishesh Gupta, Ritesh Kumar, Rajendra Pamula
Hope is considered significant for the wellbeing, recuperation and restoration of humanlife by health professionals.
no code implementations • EURALI (LREC) 2022 • Siddharth Singh, Ritesh Kumar, Shyam Ratan, Sonal Sinha
The tool provides a one-click interface to train NLP models for various tasks using the data stored in the system and then use it for assistance in further storage of the data (especially for the field linguists).
no code implementations • EMNLP (SIGTYP) 2020 • Ritesh Kumar, Deepak Alok, Akanksha Bansal, Bornini Lahiri, Atul Kr. Ojha
This paper enumerates SigTyP 2020 Shared Task on the prediction of typological features as performed by the KMI-Panlingua-IITKGP team.
no code implementations • NAACL (SIGTYP) 2021 • Andreas Scherbakov, Liam Whittle, Ritesh Kumar, Siddharth Singh, Matthew Coleman, Ekaterina Vylomova
The paper presents Anlirika’s submission to SIGTYP 2021 Shared Task on Robust Spoken Language Identification.
no code implementations • ACL (SIGMORPHON) 2021 • Tiago Pimentel, Maria Ryskina, Sabrina J. Mielke, Shijie Wu, Eleanor Chodroff, Brian Leonard, Garrett Nicolai, Yustinus Ghanggo Ate, Salam Khalifa, Nizar Habash, Charbel El-Khaissi, Omer Goldman, Michael Gasser, William Lane, Matt Coler, Arturo Oncevay, Jaime Rafael Montoya Samame, Gema Celeste Silva Villegas, Adam Ek, Jean-Philippe Bernardy, Andrey Shcherbakov, Aziyana Bayyr-ool, Karina Sheifer, Sofya Ganieva, Matvey Plugaryov, Elena Klyachko, Ali Salehi, Andrew Krizhanovsky, Natalia Krizhanovsky, Clara Vania, Sardana Ivanova, Aelita Salchak, Christopher Straughn, Zoey Liu, Jonathan North Washington, Duygu Ataman, Witold Kieraś, Marcin Woliński, Totok Suhardijanto, Niklas Stoehr, Zahroh Nuriah, Shyam Ratan, Francis M. Tyers, Edoardo M. Ponti, Grant Aiton, Richard J. Hatcher, Emily Prud'hommeaux, Ritesh Kumar, Mans Hulden, Botond Barta, Dorina Lakatos, Gábor Szolnok, Judit Ács, Mohit Raj, David Yarowsky, Ryan Cotterell, Ben Ambridge, Ekaterina Vylomova
This year's iteration of the SIGMORPHON Shared Task on morphological reinflection focuses on typological diversity and cross-lingual variation of morphosyntactic features.
no code implementations • PAIL (ICON) 2021 • Mohit Raj, Shyam Ratan, Deepak Alok, Ritesh Kumar, Atul Kr. Ojha
In this paper, we discuss the development of treebanks for two low-resourced Indian languages - Magahi and Braj - based on the Universal Dependencies framework.
no code implementations • ICON 2021 • Ritesh Kumar, Shyam Ratan, Siddharth Singh, Enakshi Nandi, Laishram Niranjana Devi, Akash Bhagat, Yogesh Dawer, Bornini Lahiri, Akanksha Bansal
If approached as three separate classification tasks, the task includes three sub-tasks: aggression identification (sub-task A), gender bias identification (sub-task B), and communal bias identification (sub-task C).
no code implementations • ICON 2021 • Siddharth Singh, Ritesh Kumar, Shyam Ratan, Sonal Sinha
Since its a web-based application, it also allows for seamless collaboration among multiple persons and sharing the data, models, etc with each other.
no code implementations • WMT (EMNLP) 2020 • Atul Kr. Ojha, Priya Rani, Akanksha Bansal, Bharathi Raja Chakravarthi, Ritesh Kumar, John P. McCrae
NUIG-Panlingua-KMI submission to WMT 2020 seeks to push the state-of-the-art in Similar Language Translation Task for Hindi↔Marathi language pair.
no code implementations • 12 Apr 2024 • Shubham Tiwari, Yash Sethia, Ritesh Kumar, Ashwani Tanwar, Rudresh Dwivedi
To mitigate these limitations, we aim to perform a holistic impact analysis of the latest filters and propose an user recognition model with the filtered images.
no code implementations • 17 Mar 2024 • Ritesh Kumar, Ojaswee Bhalla, Madhu Vanthi, Shehlat Maknoon Wani, Siddharth Singh
In this paper, we discuss the development of an annotation schema to build datasets for evaluating the offline harm potential of social media texts.
1 code implementation • 26 Dec 2023 • Laura Sisson, Aryan Amit Barsainyan, Mrityunjay Sharma, Ritesh Kumar
The application of deep learning techniques on aroma-chemicals has resulted in models more accurate than human experts at predicting olfactory qualities.
no code implementations • 3 Oct 2023 • Ritesh Kumar, Saurabh Goyal, Ashish Verma, Vatche Isahagian
\\ We present \textbf{ProtoNER}: Prototypical Network based end-to-end KVP extraction model that allows addition of new classes to an existing model while requiring minimal number of newly annotated training samples.
no code implementations • 26 Jun 2022 • Ritesh Kumar, Siddharth Singh, Shyam Ratan, Mohit Raj, Sonal Sinha, Bornini Lahiri, Vivek Seshadri, Kalika Bali, Atul Kr. Ojha
In this paper we discuss an in-progress work on the development of a speech corpus for four low-resource Indo-Aryan languages -- Awadhi, Bhojpuri, Braj and Magahi using the field methods of linguistic data collection.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • LREC 2022 • Khuyagbaatar Batsuren, Omer Goldman, Salam Khalifa, Nizar Habash, Witold Kieraś, Gábor Bella, Brian Leonard, Garrett Nicolai, Kyle Gorman, Yustinus Ghanggo Ate, Maria Ryskina, Sabrina J. Mielke, Elena Budianskaya, Charbel El-Khaissi, Tiago Pimentel, Michael Gasser, William Lane, Mohit Raj, Matt Coler, Jaime Rafael Montoya Samame, Delio Siticonatzi Camaiteri, Benoît Sagot, Esaú Zumaeta Rojas, Didier López Francis, Arturo Oncevay, Juan López Bautista, Gema Celeste Silva Villegas, Lucas Torroba Hennigen, Adam Ek, David Guriel, Peter Dirix, Jean-Philippe Bernardy, Andrey Scherbakov, Aziyana Bayyr-ool, Antonios Anastasopoulos, Roberto Zariquiey, Karina Sheifer, Sofya Ganieva, Hilaria Cruz, Ritván Karahóǧa, Stella Markantonatou, George Pavlidis, Matvey Plugaryov, Elena Klyachko, Ali Salehi, Candy Angulo, Jatayu Baxi, Andrew Krizhanovsky, Natalia Krizhanovskaya, Elizabeth Salesky, Clara Vania, Sardana Ivanova, Jennifer White, Rowan Hall Maudslay, Josef Valvoda, Ran Zmigrod, Paula Czarnowska, Irene Nikkarinen, Aelita Salchak, Brijesh Bhatt, Christopher Straughn, Zoey Liu, Jonathan North Washington, Yuval Pinter, Duygu Ataman, Marcin Wolinski, Totok Suhardijanto, Anna Yablonskaya, Niklas Stoehr, Hossep Dolatian, Zahroh Nuriah, Shyam Ratan, Francis M. Tyers, Edoardo M. Ponti, Grant Aiton, Aryaman Arora, Richard J. Hatcher, Ritesh Kumar, Jeremiah Young, Daria Rodionova, Anastasia Yemelina, Taras Andrushko, Igor Marchenko, Polina Mashkovtseva, Alexandra Serova, Emily Prud'hommeaux, Maria Nepomniashchaya, Fausto Giunchiglia, Eleanor Chodroff, Mans Hulden, Miikka Silfverberg, Arya D. McCarthy, David Yarowsky, Ryan Cotterell, Reut Tsarfaty, Ekaterina Vylomova
The project comprises two major thrusts: a language-independent feature schema for rich morphological annotation and a type-level resource of annotated data in diverse languages realizing that schema.
no code implementations • 26 Apr 2022 • Mohit Raj, Shyam Ratan, Deepak Alok, Ritesh Kumar, Atul Kr. Ojha
In this paper, we discuss the development of treebanks for two low-resourced Indian languages - Magahi and Braj based on the Universal Dependencies framework.
no code implementations • 6 Apr 2022 • Ritesh Kumar, Bornini Lahiri
In this paper, we give a summary of the resources and technologies for those Indian languages which are not included in the 8th schedule of the Indian Constitution and/or which are endangered.
no code implementations • 6 Apr 2022 • Ritesh Kumar, Atul Kr. Ojha, Bornini Lahiri, Chingrimnng Lungleng
The study is based on a corpus of slightly over 10 hours of political discourse and includes debates on news channel and political speeches.
no code implementations • 22 Mar 2022 • Siddharth Singh, Ritesh Kumar, Shyam Ratan, Sonal Sinha
The interface allows creation of multiple projects that could be shared with the other users.
no code implementations • 3 Dec 2021 • Ritesh Kumar, Girish Nath Jha
In this paper, we present a corpus based study of politeness across two languages-English and Hindi.
no code implementations • 3 Dec 2021 • Ritesh Kumar, Shiv Bhusan Kaushik, Pinkey Nainwani, Girish Nath Jha
This paper presents the challenges in creating and managing large parallel corpora of 12 major Indian languages (which is soon to be extended to 23 languages) as part of a major consortium project funded by the Department of Information Technology (DIT), Govt.
no code implementations • 30 Nov 2021 • Ritesh Kumar
Magahi is an Indo-Aryan Language, spoken mainly in the Eastern parts of India.
no code implementations • 30 Nov 2021 • Ritesh Kumar
In this paper I present a classifier for automatic identification of linguistic politeness in Hindi texts.
no code implementations • LREC 2022 • Ritesh Kumar, Enakshi Nandi, Laishram Niranjana Devi, Shyam Ratan, Siddharth Singh, Akash Bhagat, Yogesh Dawer
In this paper, we discuss the development of a multilingual dataset annotated with a hierarchical, fine-grained tagset marking different types of aggression and the "context" in which they occur.
no code implementations • 29 Oct 2021 • Ashwin Singh, Mallika Subramanian, Anmol Agarwal, Pratyush Priyadarshi, Shrey Gupta, Kiran Garimella, Sanjeev Kumar, Ritesh Kumar, Lokesh Garg, Erica Arya, Ponnurangam Kumaraguru
Our classifier achieves accuracies ranging from 79% to 90% across the five states, demonstrating its potential for assisting future ethnographic investigations.
no code implementations • 7 Aug 2021 • Poonam Adhikari, Ritesh Kumar, S. R. S Iyengar, Rishemjit Kaur
Many different technologies are used to detect pests in the crops, such as manual sampling, sensors, and radar.
no code implementations • NAACL (SIGTYP) 2021 • Elizabeth Salesky, Badr M. Abdullah, Sabrina J. Mielke, Elena Klyachko, Oleg Serikov, Edoardo Ponti, Ritesh Kumar, Ryan Cotterell, Ekaterina Vylomova
While language identification is a fundamental speech and language processing task, for many languages and language families it remains a challenging task.
1 code implementation • 11 Apr 2021 • Atul Sahay, Ayush Maheshwari, Ritesh Kumar, Ganesh Ramakrishnan, Manjesh Kumar Hanawal, Kavi Arya
In this work, we propose an attention mechanism over Tree-LSTMs to learn more meaningful and explainable parse tree structures.
1 code implementation • 17 Sep 2020 • Siddharth Bhatia, Arjit Jain, Pan Li, Ritesh Kumar, Bryan Hooi
Given a stream of entries in a multi-aspect data setting i. e., entries having multiple dimensions, how can we detect anomalous activities in an unsupervised manner?
Ranked #1 on Intrusion Detection on CIC-DDoS
no code implementations • LREC 2020 • Ritesh Kumar, Atul Kr. Ojha, Shervin Malmasi, Marcos Zampieri
The task consisted of two sub-tasks - aggression identification (sub-task A) and gendered identification (sub-task B) - in three languages - Bangla, Hindi and English.
no code implementations • LREC 2020 • Shiladitya Bhattacharya, Siddharth Singh, Ritesh Kumar, Akanksha Bansal, Akash Bhagat, Yogesh Dawer, Bornini Lahiri, Atul Kr. Ojha
In this paper, we discuss the development of a multilingual annotated corpus of misogyny and aggression in Indian English, Hindi, and Indian Bangla as part of a project on studying and automatically identifying misogyny and communalism on social media (the ComMA Project).
no code implementations • 19 Aug 2019 • Ayush Maheshwari, Hrishikesh Patel, Nandan Rathod, Ritesh Kumar, Ganesh Ramakrishnan, Pushpak Bhattacharyya
The problem of event extraction is a relatively difficult task for low resource languages due to the non-availability of sufficient annotated data.
no code implementations • WS 2019 • Atul Kr. Ojha, Ritesh Kumar, Akanksha Bansal, Priya Rani
The present paper enumerates the development of Panlingua-KMI Machine Translation (MT) systems for Hindi ↔ Nepali language pair, designed as part of the Similar Language Translation Task at the WMT 2019 Shared Task.
1 code implementation • 10 Jun 2019 • Yi Ren Fung, Ziqiang Guan, Ritesh Kumar, Joie Yeahuay Wu, Madalina Fiterau
In recent years, many papers have reported state-of-the-art performance on Alzheimer's Disease classification with MRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset using convolutional neural networks.
no code implementations • SEMEVAL 2019 • Ritesh Kumar, Guggilla Bhanodai, Rajendra Pamula, Maheswara Reddy Chennuru
This paper describes the work that our team bhanodaig did at Indian Institute of Technology (ISM) towards OffensEval i. e. identifying and categorizing offensive language in social media.
no code implementations • 16 Apr 2019 • Ziqiang Guan, Ritesh Kumar, Yi Ren Fung, Yeahuay Wu, Madalina Fiterau
A plethora of deep learning models have been developed for the task of Alzheimer's disease classification from brain MRI scans.
2 code implementations • SEMEVAL 2019 • Marcos Zampieri, Shervin Malmasi, Preslav Nakov, Sara Rosenthal, Noura Farra, Ritesh Kumar
We present the results and the main findings of SemEval-2019 Task 6 on Identifying and Categorizing Offensive Language in Social Media (OffensEval).
2 code implementations • NAACL 2019 • Marcos Zampieri, Shervin Malmasi, Preslav Nakov, Sara Rosenthal, Noura Farra, Ritesh Kumar
In particular, we model the task hierarchically, identifying the type and the target of offensive messages in social media.
no code implementations • COLING 2018 • Ritesh Kumar, Manas Jyoti Bora
In this paper, we discuss the development of a part-of-speech tagger for English-Assamese code-mixed texts.
no code implementations • COLING 2018 • Marcos Zampieri, Shervin Malmasi, Preslav Nakov, Ahmed Ali, Suwon Shon, James Glass, Yves Scherrer, Tanja Samard{\v{z}}i{\'c}, Nikola Ljube{\v{s}}i{\'c}, J{\"o}rg Tiedemann, Chris van der Lee, Stefan Grondelaers, Nelleke Oostdijk, Dirk Speelman, Antal Van den Bosch, Ritesh Kumar, Bornini Lahiri, Mayank Jain
We present the results and the findings of the Second VarDial Evaluation Campaign on Natural Language Processing (NLP) for Similar Languages, Varieties and Dialects.
no code implementations • COLING 2018 • Ritesh Kumar, Guggilla Bhanodai, Rajendra Pamula, Maheshwar Reddy Chennuru
This paper describes the work that our team bhanodaig did at Indian Institute of Technology (ISM) towards TRAC-1 Shared Task on Aggression Identification in Social Media for COLING 2018.
no code implementations • COLING 2018 • Ritesh Kumar, Atul Kr. Ojha, Shervin Malmasi, Marcos Zampieri
For this task, the participants were provided with a dataset of 15, 000 aggression-annotated Facebook Posts and Comments each in Hindi (in both Roman and Devanagari script) and English for training and validation.
no code implementations • LREC 2018 • Ritesh Kumar, Aishwarya N. Reganti, Akshit Bhatia, Tushar Maheshwari
As the interaction over the web has increased, incidents of aggression and related events like trolling, cyberbullying, flaming, hate speech, etc.
no code implementations • 26 Mar 2018 • Ritesh Kumar, Bornini Lahiri, Deepak Alok, Atul Kr. Ojha, Mayank Jain, Abdul Basit, Yogesh Dawer
In this paper, we discuss an attempt to develop an automatic language identification system for 5 closely-related Indo-Aryan languages of India, Awadhi, Bhojpuri, Braj, Hindi and Magahi.
no code implementations • LREC 2014 • Ritesh Kumar
In this paper I discuss the creation and annotation of a corpus of Hindi blogs.
no code implementations • LREC 2012 • Ritesh Kumar
The present paper describes an ongoing effort to compile and annotate a large corpus of computer-mediated communication (CMC) in Hindi.