Search Results for author: Pushpak Bhattacharyya

Found 386 papers, 44 papers with code

IIITBH-IITP@CL-SciSumm20, CL-LaySumm20, LongSumm20

no code implementations EMNLP (sdp) 2020 Saichethan Reddy, Naveen Saini, Sriparna Saha, Pushpak Bhattacharyya

In this paper, we present the IIIT Bhagalpur and IIT Patna team’s effort to solve the three shared tasks namely, CL-SciSumm 2020, CL-LaySumm 2020, LongSumm 2020 at SDP 2020.

SEPRG: Sentiment aware Emotion controlled Personalized Response Generation

no code implementations INLG (ACL) 2021 Mauajama Firdaus, Umang Jain, Asif Ekbal, Pushpak Bhattacharyya

We design a Transformer based Dialogue Generation framework, that generates responses that are sensitive to the emotion of the user and corresponds to the persona and sentiment as well.

Dialogue Generation Response Generation

Zero-shot Disfluency Detection for Indian Languages

no code implementations COLING 2022 Rohit Kundu, Preethi Jyothi, Pushpak Bhattacharyya

We present a detailed pipeline to synthetically generate disfluent text and create evaluation datasets for four Indian languages: Bengali, Hindi, Malayalam, and Marathi.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Emotion Enriched Retrofitted Word Embeddings

no code implementations COLING 2022 Sapan Shah, Sreedhar Reddy, Pushpak Bhattacharyya

The retrofitted embeddings achieve better inter-cluster and intra-cluster distance for words having the same emotions, e. g., the joy cluster containing words like fun, happiness, etc., and the anger cluster with words like offence, rage, etc., as evaluated through different cluster quality metrics.

Sarcasm Detection Sentiment Analysis +1

HindiMD: A Multi-domain Corpora for Low-resource Sentiment Analysis

no code implementations LREC 2022 Mamta ., Asif Ekbal, Pushpak Bhattacharyya, Tista Saha, Alka Kumar, Shikha Srivastava

Social media platforms such as Twitter have evolved into a vast information sharing platform, allowing people from a variety of backgrounds and expertise to share their opinions on numerous events such as terrorism, narcotics and many other social issues.

Sentiment Analysis

Novelty Detection: A Perspective from Natural Language Processing

no code implementations CL (ACL) 2022 Tirthankar Ghosal, Tanik Saikh, Tameesh Biswas, Asif Ekbal, Pushpak Bhattacharyya

In this work, we build upon our earlier investigations for document-level novelty detection and present a comprehensive account of our efforts toward the problem.

Natural Language Inference Novelty Detection

pyiwn: A Python based API to access Indian Language WordNets

no code implementations GWC 2018 Ritesh Panjwani, Diptesh Kanojia, Pushpak Bhattacharyya

Indian language WordNets have their individual web-based browsing interfaces along with a common interface for IndoWordNet.

Speech Synthesis

Synthesizing Audio for Hindi WordNet

no code implementations GWC 2018 Diptesh Kanojia, Preethi Jyothi, Pushpak Bhattacharyya

We also develop voices using the existing implementations of the aforementioned systems, and (2) We use these voices to generate sample audios for randomly chosen words; manually evaluate the audio generated, and produce audio for all WordNet words using the winner voice model.

Speech Synthesis

Modelling Source- and Target- Language Syntactic Information as Conditional Context in Interactive Neural Machine Translation

no code implementations EAMT 2020 Kamal Kumar Gupta, Rejwanul Haque, Asif Ekbal, Pushpak Bhattacharyya, Andy Way

In this study, we model source-language syntactic constituency parse and target-language syntactic descriptions in the form of supertags as conditional context for interactive prediction in neural MT (NMT).

Machine Translation NMT +1

IITP-AI-NLP-ML@ CL-SciSumm 2020, CL-LaySumm 2020, LongSumm 2020

no code implementations EMNLP (sdp) 2020 Santosh Kumar Mishra, Harshavardhan Kundarapu, Naveen Saini, Sriparna Saha, Pushpak Bhattacharyya

The publication rate of scientific literature increases rapidly, which poses a challenge for researchers to keep themselves updated with new state-of-the-art.

Decoder Document Summarization +3

Retrofitting of Pre-trained Emotion Words with VAD-dimensions and the Plutchik Emotions

no code implementations ICON 2021 Manasi Kulkarni, Pushpak Bhattacharyya

This is a lexicons based approach that uses the Valence, Arousal and Dominance (VAD) values, and the Plutchik’s emotions to incorporate the emotion information in pre-trained word embeddings using post-training processing.

Emotion Recognition Word Embeddings

A Scaled Encoder Decoder Network for Image Captioning in Hindi

no code implementations ICON 2021 Santosh Kumar Mishra, Sriparna Saha, Pushpak Bhattacharyya

The proposed method’s performance is compared with state-of-the-art methods in terms of BLEU scores and manual evaluation (in terms of adequacy and fluency).

Decoder Image Captioning

High, Medium or Low? Detecting Intensity Variation Among polar synonyms in WordNet

no code implementations GWC 2016 Raksha Sharma, Pushpak Bhattacharyya

For fine-grained sentiment analysis, we need to go beyond zero-one polarity and find a way to compare adjectives (synonyms) that share the same sense.

Sentiment Analysis

IndoWordNet Conversion to Web Ontology Language (OWL)

no code implementations GWC 2016 Apurva Nagvenkar, Jyoti Pawar, Pushpak Bhattacharyya

In this paper, we present a data representation of IndoWordNet in Web Ontology Language (OWL).

Mapping it differently: A solution to the linking challenges

no code implementations GWC 2016 Meghna Singh, Rajita Shukla, Jaya Saraswati, Laxmi Kashyap, Diptesh Kanojia, Pushpak Bhattacharyya

This paper reports the work of creating bilingual mappings in English for certain synsets of Hindi wordnet, the need for doing this, the methods adopted and the tools created for the task.

Information Retrieval Retrieval +4

BERT based Adverse Drug Effect Tweet Classification

no code implementations NAACL (SMM4H) 2021 Tanay Kayastha, Pranjal Gupta, Pushpak Bhattacharyya

This paper describes models developed for the Social Media Mining for Health (SMM4H) 2021 shared tasks.

Classification

“So You Think You’re Funny?”: Rating the Humour Quotient in Standup Comedy

1 code implementation EMNLP 2021 Anirudh Mittal, Pranav Jeevan P, Prerak Gandhi, Diptesh Kanojia, Pushpak Bhattacharyya

The normalized duration (laughter duration divided by the clip duration) of laughter in each clip is used to compute this humour coefficient score on a five-point scale (0-4).

A Deep Ensemble Framework for Fake News Detection and Multi-Class Classification of Short Political Statements

no code implementations ICON 2019 Arjun Roy, Kingshuk Basak, Asif Ekbal, Pushpak Bhattacharyya

Fake news, rumor, incorrect information, and misinformation detection are nowadays crucial issues as these might have serious consequences for our social fabrics.

Fake News Detection Misinformation +1

Multiple Pivot Languages and Strategic Decoder Initialization Helps Neural Machine Translation

no code implementations loresmt (COLING) 2022 Shivam Mhaskar, Pushpak Bhattacharyya

In pivot-based transfer learning, the source to pivot and the pivot to target models are used to improve the performance of the source to target model.

Decoder Machine Translation +2

Team IITP-AINLPML at WASSA 2022: Empathy Detection, Emotion Classification and Personality Detection

no code implementations WASSA (ACL) 2022 Soumitra Ghosh, Dhirendra Maurya, Asif Ekbal, Pushpak Bhattacharyya

Computational comprehension and identifying emotional components in language have been critical in enhancing human-computer connection in recent years.

Emotion Classification

Pivot Based Transfer Learning for Neural Machine Translation: CFILT IITB @ WMT 2021 Triangular MT

no code implementations WMT (EMNLP) 2021 Shivam Mhaskar, Pushpak Bhattacharyya

Such a large amount of parallel corpus is majorly available for language pairs which include English and not for non-English language pairs.

Decoder Machine Translation +2

A Multi-task Model for Multilingual Trigger Detection and Classification

no code implementations ICON 2019 Sovan Kumar Sahoo, Saumajit Saha, Asif Ekbal, Pushpak Bhattacharyya

In this paper we present a deep multi-task learning framework for multilingual event and argument trigger detection and classification.

Classification Multi-Task Learning

Looks can be Deceptive: Distinguishing Repetition Disfluency from Reduplication

no code implementations11 Jul 2024 Arif Ahmad, Mothika Gayathri Khyathi, Pushpak Bhattacharyya

Our models achieve macro F1 scores of up to 85. 62% in Hindi, 83. 95% in Telugu, and 84. 82% in Marathi for reduplication-repetition classification.

token-classification Token Classification

Beyond Aesthetics: Cultural Competence in Text-to-Image Models

1 code implementation9 Jul 2024 Nithish Kannen, Arif Ahmad, Marco Andreetto, Vinodkumar Prabhakaran, Utsav Prabhu, Adji Bousso Dieng, Pushpak Bhattacharyya, Shachi Dave

CUBE consists of 1) CUBE-1K, a set of high-quality prompts that enable the evaluation of cultural awareness, and 2) CUBE-CSpace, a larger dataset of cultural artifacts that serves as grounding to evaluate cultural diversity.

Diversity

ConCodeEval: Evaluating Large Language Models for Code Constraints in Domain-Specific Languages

no code implementations3 Jul 2024 Mehant Kammakomati, Sameer Pimparkhede, Srikanth Tamilselvam, Prince Kumar, Pushpak Bhattacharyya

Recent work shows Large Language Models (LLMs) struggle to understand natural language constraints for various text generation tasks in zero- and few-shot settings.

Text Generation

A Case Study on Context-Aware Neural Machine Translation with Multi-Task Learning

no code implementations3 Jul 2024 Ramakrishna Appicharla, Baban Gain, Santanu Pal, Asif Ekbal, Pushpak Bhattacharyya

Evaluation results show that the proposed MTL approach performs better than concatenation-based and multi-encoder DocNMT models in low-resource settings and is sensitive to the choice of context.

Machine Translation Multi-Task Learning +1

"I understand why I got this grade": Automatic Short Answer Grading with Feedback

no code implementations30 Jun 2024 Dishank Aggarwal, Pushpak Bhattacharyya, Bhaskaran Raman

The demand for efficient and accurate assessment methods has intensified as education systems transition to digital platforms.

How effective is Multi-source pivoting for Translation of Low Resource Indian Languages?

no code implementations19 Jun 2024 Pranav Gaikwad, Meet Doshi, Raj Dabre, Pushpak Bhattacharyya

Machine Translation (MT) between linguistically dissimilar languages is challenging, especially due to the scarcity of parallel corpora.

Machine Translation Sentence +1

DocCGen: Document-based Controlled Code Generation

no code implementations17 Jun 2024 Sameer Pimparkhede, Mehant Kammakomati, Srikanth Tamilselvam, Prince Kumar, Ashok Pon Kumar, Pushpak Bhattacharyya

However, it suffers from problems, such as limited DSL samples and prompt sensitivity but enterprises maintain good documentation of the DSLs.

Code Generation In-Context Learning

Mental Disorder Classification via Temporal Representation of Text

no code implementations15 Jun 2024 Raja Kumar, Kishan Maharaj, Ashita Saxena, Pushpak Bhattacharyya

Mental disorder prediction from social media posts by current LLMs is challenging due to the complexities of sequential text data and the limited context length of language models.

Classification Language Modelling

Facts-and-Feelings: Capturing both Objectivity and Subjectivity in Table-to-Text Generation

no code implementations15 Jun 2024 Tathagata Dey, Pushpak Bhattacharyya

We perform the task of fine-tuning sequence-to-sequence models on the linearized tables and prompting on popular large language models.

Table-to-Text Generation

Precision Empowers, Excess Distracts: Visual Question Answering With Dynamically Infused Knowledge In Language Models

no code implementations14 Jun 2024 Manas Jhalani, Annervaz K M, Pushpak Bhattacharyya

Knowledge-Based Visual Question Answering (KBVQA) advances this concept by adding external knowledge along with images to respond to questions.

Decoder Knowledge Graphs +3

MemeGuard: An LLM and VLM-based Framework for Advancing Content Moderation via Meme Intervention

1 code implementation8 Jun 2024 Prince Jha, Raghav Jain, Konika Mandal, Aman Chadha, Sriparna Saha, Pushpak Bhattacharyya

In the digital world, memes present a unique challenge for content moderation due to their potential to spread harmful content.

Seeing the Unseen: Visual Metaphor Captioning for Videos

no code implementations7 Jun 2024 Abisek Rajakumar Kalarani, Pushpak Bhattacharyya, Sumit Shekhar

As of now, no probing studies have been done that involve complex language phenomena like metaphors with videos.

ToxVidLM: A Multimodal Framework for Toxicity Detection in Code-Mixed Videos

1 code implementation31 May 2024 Krishanu Maity, A. S. Poornash, Sriparna Saha, Pushpak Bhattacharyya

In an era of rapidly evolving internet technology, the surge in multimodal content, including videos, has expanded the horizons of online communication.

Video Classification

Striking a Balance between Classical and Deep Learning Approaches in Natural Language Processing Pedagogy

no code implementations16 May 2024 Aditya Joshi, Jake Renzella, Pushpak Bhattacharyya, Saurav Jha, Xiangyu Zhang

While deep learning approaches represent the state-of-the-art of natural language processing (NLP) today, classical algorithms and approaches still find a place in NLP textbooks and courses of recent years.

A Morphology-Based Investigation of Positional Encodings

no code implementations6 Apr 2024 Poulami Ghosh, Shikhar Vashishth, Raj Dabre, Pushpak Bhattacharyya

Contemporary deep learning models effectively handle languages with diverse morphology despite not being directly integrated into them.

Dependency Parsing named-entity-recognition +3

Do Not Worry if You Do Not Have Data: Building Pretrained Language Models Using Translationese

no code implementations20 Mar 2024 Meet Doshi, Raj Dabre, Pushpak Bhattacharyya

In this paper, we explore the utility of Translationese as synthetic data created using machine translation for pre-training language models (LMs).

Machine Translation Natural Language Understanding

Material Microstructure Design Using VAE-Regression with Multimodal Prior

no code implementations27 Feb 2024 Avadhut Sardeshmukh, Sreedhar Reddy, BP Gautham, Pushpak Bhattacharyya

The resultant model can be used for both forward and inverse prediction i. e., for predicting the properties of a given microstructure as well as for predicting the microstructure required to obtain given properties.

Property Prediction regression

One Prompt To Rule Them All: LLMs for Opinion Summary Evaluation

1 code implementation18 Feb 2024 Tejpalsingh Siledar, Swaroop Nath, Sankara Sri Raghava Ravindra Muddu, Rupasai Rangaraju, Swaprava Nath, Pushpak Bhattacharyya, Suman Banerjee, Amey Patil, Sudhanshu Shekhar Singh, Muthusamy Chelliah, Nikesh Garera

Evaluation of opinion summaries using conventional reference-based metrics rarely provides a holistic evaluation and has been shown to have a relatively low correlation with human judgments.

nlg evaluation Opinion Summarization +1

Meme-ingful Analysis: Enhanced Understanding of Cyberbullying in Memes Through Multimodal Explanations

1 code implementation18 Jan 2024 Prince Jha, Krishanu Maity, Raghav Jain, Apoorv Verma, Sriparna Saha, Pushpak Bhattacharyya

A Contrastive Language-Image Pretraining (CLIP) projection-based multimodal shared-private multitask approach has been proposed for visual and textual explanation of a meme.

Explain Thyself Bully: Sentiment Aided Cyberbullying Detection with Explanation

1 code implementation17 Jan 2024 Krishanu Maity, Prince Jha, Raghav Jain, Sriparna Saha, Pushpak Bhattacharyya

While plenty of research is going on to develop better models for cyberbullying detection in monolingual language, there is very little research on the code-mixed languages and explainability aspect of cyberbullying.

Sentence Sentiment Analysis

PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics Capabilities

no code implementations13 Jan 2024 Settaluri Lakshmi Sravanthi, Meet Doshi, Tankala Pavan Kalyan, Rudra Murthy, Pushpak Bhattacharyya, Raj Dabre

To demonstrate this fact, we release a Pragmatics Understanding Benchmark (PUB) dataset consisting of fourteen tasks in four pragmatics phenomena, namely, Implicature, Presupposition, Reference, and Deixis.

Instruction Following Multiple-choice

Yes, this is what I was looking for! Towards Multi-modal Medical Consultation Concern Summary Generation

1 code implementation10 Jan 2024 Abhisek Tiwari, Shreyangshu Bera, Sriparna Saha, Pushpak Bhattacharyya, Samrat Ghosh

Over the past few years, the use of the Internet for healthcare-related tasks has grown by leaps and bounds, posing a challenge in effectively managing and processing information to ensure its efficient utilization.

Intent Recognition

IndicIRSuite: Multilingual Dataset and Neural Information Models for Indian Languages

1 code implementation15 Dec 2023 Saiful Haq, Ashutosh Sharma, Pushpak Bhattacharyya

To the best of our knowledge, IndicIRSuite is the first attempt at building large-scale Neural Information Retrieval resources for a large number of Indian languages, and we hope that it will help accelerate research in Neural IR for Indian Languages.

Information Retrieval Machine Translation +1

Retrofitting Light-weight Language Models for Emotions using Supervised Contrastive Learning

no code implementations29 Oct 2023 Sapan Shah, Sreedhar Reddy, Pushpak Bhattacharyya

We present a novel retrofitting method to induce emotion aspects into pre-trained language models (PLMs) such as BERT and RoBERTa.

Contrastive Learning Few-Shot Learning +3

DISCO: A Large Scale Human Annotated Corpus for Disfluency Correction in Indo-European Languages

1 code implementation25 Oct 2023 Vineet Bhat, Preethi Jyothi, Pushpak Bhattacharyya

Towards the goal of multilingual disfluency correction, we present a high-quality human-annotated DC corpus covering four important Indo-European languages: English, Hindi, German and French.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Sarcasm in Sight and Sound: Benchmarking and Expansion to Improve Multimodal Sarcasm Detection

no code implementations29 Sep 2023 Swapnil Bhosale, Abhra Chaudhuri, Alex Lee Robert Williams, Divyank Tiwari, Anjan Dutta, Xiatian Zhu, Pushpak Bhattacharyya, Diptesh Kanojia

The introduction of the MUStARD dataset, and its emotion recognition extension MUStARD++, have identified sarcasm to be a multi-modal phenomenon -- expressed not only in natural language text, but also through manners of speech (like tonality and intonation) and visual cues (facial expression).

Benchmarking Diversity +2

Experience and Evidence are the eyes of an excellent summarizer! Towards Knowledge Infused Multi-modal Clinical Conversation Summarization

1 code implementation27 Sep 2023 Abhisek Tiwari, Anisha Saha, Sriparna Saha, Pushpak Bhattacharyya, Minakshi Dhar

We propose a knowledge-infused, multi-modal, multi-tasking medical domain identification and clinical conversation summary generation (MM-CliConSummation) framework.

"Beware of deception": Detecting Half-Truth and Debunking it through Controlled Claim Editing

no code implementations15 Aug 2023 Sandeep Singamsetty, Nishtha Madaan, Sameep Mehta, Varad Bhatnagar, Pushpak Bhattacharyya

To help combat this problem, we have created a comprehensive pipeline consisting of a half-truth detection model and a claim editing model.

KITLM: Domain-Specific Knowledge InTegration into Language Models for Question Answering

1 code implementation7 Aug 2023 Ankush Agarwal, Sakharam Gawade, Amar Prakash Azad, Pushpak Bhattacharyya

Our research contributes to advancing the field of domain-specific language understanding and showcases the potential of knowledge infusion techniques in improving the performance of language models on question-answering.

Language Modelling Multi-hop Question Answering +1

Decision Knowledge Graphs: Construction of and Usage in Question Answering for Clinical Practice Guidelines

no code implementations6 Aug 2023 Vasudhan Varma Kandula, Pushpak Bhattacharyya

In this paper, we present a Decision Knowledge Graph (DKG) representation to store CPGs and to perform question-answering on CPGs.

Knowledge Graphs Question Answering

"Kurosawa": A Script Writer's Assistant

no code implementations6 Aug 2023 Prerak Gandhi, Vishal Pramanik, Pushpak Bhattacharyya

We fine-tune GPT-3 with the above datasets to generate plots and scenes.

"We care": Improving Code Mixed Speech Emotion Recognition in Customer-Care Conversations

no code implementations6 Aug 2023 N V S Abhishek, Pushpak Bhattacharyya

Emotion recognition is essential in building robust conversational agents in domains such as law, healthcare, education, and customer support.

Speech Emotion Recognition

"A Little is Enough": Few-Shot Quality Estimation based Corpus Filtering improves Machine Translation

no code implementations6 Jun 2023 Akshay Batheja, Pushpak Bhattacharyya

To the best of our knowledge, this is a novel adaptation of the QE framework to extract quality parallel corpus from the pseudo-parallel corpus.

Machine Translation Sentence +2

"Let's not Quote out of Context": Unified Vision-Language Pretraining for Context Assisted Image Captioning

no code implementations1 Jun 2023 Abisek Rajakumar Kalarani, Pushpak Bhattacharyya, Niyati Chhaya, Sumit Shekhar

We exploit context by pretraining our model with datasets of three tasks: news image captioning where the news article is the context, contextual visual entailment, and keyword extraction from the context.

Image Captioning Keyword Extraction +2

A Match Made in Heaven: A Multi-task Framework for Hyperbole and Metaphor Detection

1 code implementation27 May 2023 Naveen Badathala, Abisek Rajakumar Kalarani, Tejpalsingh Siledar, Pushpak Bhattacharyya

Additionally, our multi-task learning (MTL) approach shows an improvement of up to 17% over single-task learning (STL) for both hyperbole and metaphor detection, supporting our hypothesis.

Multi-Task Learning

VAKTA-SETU: A Speech-to-Speech Machine Translation Service in Select Indic Languages

no code implementations21 May 2023 Shivam Mhaskar, Vineet Bhat, Akshay Batheja, Sourabh Deoghare, Paramveer Choudhary, Pushpak Bhattacharyya

In this work, we present our deployment-ready Speech-to-Speech Machine Translation (SSMT) system for English-Hindi, English-Marathi, and Hindi-Marathi language pairs.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +5

Denoising-based UNMT is more robust to word-order divergence than MASS-based UNMT

no code implementations2 Mar 2023 Tamali Banerjee, Rudra Murthy V, Pushpak Bhattacharyya

We aim to investigate whether UNMT approaches with self-supervised pre-training are robust to word-order divergence between language pairs.

Denoising Translation

Improving Machine Translation with Phrase Pair Injection and Corpus Filtering

no code implementations19 Jan 2023 Akshay Batheja, Pushpak Bhattacharyya

In this paper, we show that the combination of Phrase Pair Injection and Corpus Filtering boosts the performance of Neural Machine Translation (NMT) systems.

Machine Translation NMT +1

Detecting Unintended Social Bias in Toxic Language Datasets

no code implementations21 Oct 2022 Nihar Sahoo, Himanshu Gupta, Pushpak Bhattacharyya

However, very little research has been done to detect unintended social bias from these toxic language datasets.

Knowledge Graph Construction and Its Application in Automatic Radiology Report Generation from Radiologist's Dictation

no code implementations13 Jun 2022 Kaveri Kale, Pushpak Bhattacharyya, Aditya Shetty, Milind Gune, Kush Shrivastava, Rustom Lawyer, Spriha Biswas

Then the transcriptionist prepares a preliminary formatted report referring to the notes, and finally, the radiologist reviews the report, corrects the errors, and signs off.

graph construction Semantic Similarity +1

Hollywood Identity Bias Dataset: A Context Oriented Bias Analysis of Movie Dialogues

no code implementations LREC 2022 Sandhya Singh, Prapti Roy, Nihar Sahoo, Niteesh Mallela, Himanshu Gupta, Pushpak Bhattacharyya, Milind Savagaonkar, Nidhi, Roshni Ramnani, Anutosh Maitra, Shubhashis Sengupta

Since AI solutions are data intensive and there exists no domain specific data to address the problem of biases in scripts, we introduce a new dataset of movie scripts that are annotated for identity bias.

Am I No Good? Towards Detecting Perceived Burdensomeness and Thwarted Belongingness from Suicide Notes

no code implementations20 May 2022 Soumitra Ghosh, Asif Ekbal, Pushpak Bhattacharyya

The World Health Organization (WHO) has emphasized the importance of significantly accelerating suicide prevention efforts to fulfill the United Nations' Sustainable Development Goal (SDG) objective of 2030.

HiNER: A Large Hindi Named Entity Recognition Dataset

1 code implementation LREC 2022 Rudra Murthy, Pallab Bhattacharjee, Rahul Sharnagat, Jyotsana Khatri, Diptesh Kanojia, Pushpak Bhattacharyya

We use different language models to perform the sequence labelling task for NER and show the efficacy of our data by performing a comparative evaluation with models trained on another dataset available for the Hindi NER task.

named-entity-recognition Named Entity Recognition +2

Indian Language Wordnets and their Linkages with Princeton WordNet

no code implementations LREC 2018 Diptesh Kanojia, Kevin Patel, Pushpak Bhattacharyya

Linked wordnets are extensions of wordnets, which link similar concepts in wordnets of different languages.

Strategies of Effective Digitization of Commentaries and Sub-commentaries: Towards the Construction of Textual History

no code implementations5 Jan 2022 Diptesh Kanojia, Malhar Kulkarni, Sayali Ghodekar, Eivind Kahrs, Pushpak Bhattacharyya

We use the text of the K\=a\'sik\=avrtti (KV) as a sample text, and with the help of philologists, we digitize the commentaries available to us.

Utilizing Wordnets for Cognate Detection among Indian Languages

no code implementations GWC 2019 Diptesh Kanojia, Kevin Patel, Pushpak Bhattacharyya, Malhar Kulkarni, Gholamreza Haffari

Automatic Cognate Detection (ACD) is a challenging task which has been utilized to help NLP applications like Machine Translation, Information Retrieval and Computational Phylogenetics.

Information Retrieval Machine Translation +1

Challenge Dataset of Cognates and False Friend Pairs from Indian Languages

1 code implementation LREC 2020 Diptesh Kanojia, Pushpak Bhattacharyya, Malhar Kulkarni, Gholamreza Haffari

In this paper, we describe the creation of two cognate datasets for twelve Indian languages, namely Sanskrit, Hindi, Assamese, Oriya, Kannada, Gujarati, Tamil, Telugu, Punjabi, Bengali, Marathi, and Malayalam.

Information Retrieval Machine Translation +2

Tapping BERT for Preposition Sense Disambiguation

no code implementations27 Nov 2021 Siddhesh Pawar, Shyam Thombre, Anirudh Mittal, Girishkumar Ponkiya, Pushpak Bhattacharyya

In this paper, we propose a novel methodology for preposition sense disambiguation (PSD), which does not use any linguistic tools.

Question Answering

"So You Think You're Funny?": Rating the Humour Quotient in Standup Comedy

1 code implementation25 Oct 2021 Anirudh Mittal, Pranav Jeevan, Prerak Gandhi, Diptesh Kanojia, Pushpak Bhattacharyya

We devise a novel scoring mechanism to annotate the training data with a humour quotient score using the audience's laughter.

COVIDRead: A Large-scale Question Answering Dataset on COVID-19

no code implementations5 Oct 2021 Tanik Saikh, Sovan Kumar Sahoo, Asif Ekbal, Pushpak Bhattacharyya

This dataset creates a new avenue of carrying out research on COVID-19 by providing a benchmark dataset and a baseline model.

Question Answering

M2H2: A Multimodal Multiparty Hindi Dataset For Humor Recognition in Conversations

1 code implementation3 Aug 2021 Dushyant Singh Chauhan, Gopendra Vikram Singh, Navonil Majumder, Amir Zadeh, Asif Ekbal, Pushpak Bhattacharyya, Louis-Philippe Morency, Soujanya Poria

We propose several strong multimodal baselines and show the importance of contextual and multimodal information for humor recognition in conversations.

Dialogue Understanding

Crosslingual Embeddings are Essential in UNMT for Distant Languages: An English to IndoAryan Case Study

no code implementations MTSummit 2021 Tamali Banerjee, Rudra Murthy V, Pushpak Bhattacharyya

In this paper, we show that initializing the embedding layer of UNMT models with cross-lingual embeddings shows significant improvements in BLEU score over existing approaches with embeddings randomly initialized.

Denoising Translation +1

Towards Sentiment and Emotion aided Multi-modal Speech Act Classification in Twitter

no code implementations NAACL 2021 Tulika Saha, Apoorva Upadhyaya, Sriparna Saha, Pushpak Bhattacharyya

Experimental results indicate that the proposed framework boosts the performance of the primary task, i. e., TA classification (TAC) by benefitting from the two secondary tasks, i. e., Sentiment and Emotion Analysis compared to its uni-modal and single task TAC (tweet act classification) variants.

Classification Emotion Recognition

Semantic Extractor-Paraphraser based Abstractive Summarization

no code implementations ICON 2020 Anubhav Jangra, Raghav Jain, Vaibhav Mavi, Sriparna Saha, Pushpak Bhattacharyya

The anthology of spoken languages today is inundated with textual information, necessitating the development of automatic summarization models.

Abstractive Text Summarization

Modelling Context Emotions using Multi-task Learning for Emotion Controlled Dialog Generation

no code implementations EACL 2021 Deeksha Varshney, Asif Ekbal, Pushpak Bhattacharyya

We employ multi-task learning to predict the emotion label and to generate a viable response for a given utterance using a common encoder with multiple decoders.

Decoder Multi-Task Learning +2

Techniques for Jointly Extracting Entities and Relations: A Survey

no code implementations10 Mar 2021 Sachin Pawar, Pushpak Bhattacharyya, Girish K. Palshikar

Traditionally, relation extraction is carried out after entity extraction in a "pipeline" fashion, so that relation extraction only focuses on determining whether any semantic relation exists between a pair of extracted entity mentions.

Relation Relation Extraction

Knowledge-based Extraction of Cause-Effect Relations from Biomedical Text

no code implementations10 Mar 2021 Sachin Pawar, Ravina More, Girish K. Palshikar, Pushpak Bhattacharyya, Vasudeva Varma

We propose a knowledge-based approach for extraction of Cause-Effect (CE) relations from biomedical text.

Cognitively Aided Zero-Shot Automatic Essay Grading

no code implementations ICON 2020 Sandeep Mathias, Rudra Murthy, Diptesh Kanojia, Pushpak Bhattacharyya

Automatic essay grading (AEG) is a process in which machines assign a grade to an essay written in response to a topic, called the prompt.

EmotionGIF-IITP-AINLPML: Ensemble-based Automated Deep Neural System for predicting category(ies) of a GIF response

no code implementations23 Dec 2020 Soumitra Ghosh, Arkaprava Roy, Asif Ekbal, Pushpak Bhattacharyya

In this paper, we describe the systems submitted by our IITP-AINLPML team in the shared task of SocialNLP 2020, EmotionGIF 2020, on predicting the category(ies) of a GIF response for a given unlabelled tweet.

A Retrofitting Model for Incorporating Semantic Relations into Word Embeddings

no code implementations COLING 2020 Sapan Shah, Sreedhar Reddy, Pushpak Bhattacharyya

We present a novel retrofitting model that can leverage relational knowledge available in a knowledge resource to improve word embeddings.

Lexical Entailment Metric Learning +2

IITP-AINLPML at SemEval-2020 Task 12: Offensive Tweet Identification and Target Categorization in a Multitask Environment

no code implementations SEMEVAL 2020 Soumitra Ghosh, Asif Ekbal, Pushpak Bhattacharyya

In this paper, we describe the participation of IITP-AINLPML team in the SemEval-2020 SharedTask 12 on Offensive Language Identification and Target Categorization in English Twitter data.

Language Identification

EL-BERT at SemEval-2020 Task 10: A Multi-Embedding Ensemble Based Approach for Emphasis Selection in Visual Media

no code implementations SEMEVAL 2020 Chandresh Kanani, Sriparna Saha, Pushpak Bhattacharyya

Emphasis selection is the task of choosing candidate words for emphasis, it helps in automatically designing posters and other media contents with written text.

valid

Assessing the Severity of Health States based on Social Media Posts

no code implementations21 Sep 2020 Shweta Yadav, Joy Prakash Sain, Amit Sheth, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya

The diverse NLU views demonstrate its effectiveness on both the tasks and as well as on the individual disease to assess a user's health.

Multiview Learning Natural Language Understanding

Sentiment and Emotion help Sarcasm? A Multi-task Learning Framework for Multi-Modal Sarcasm, Sentiment and Emotion Analysis

no code implementations ACL 2020 Dushyant Singh Chauhan, Dhanush S R, Asif Ekbal, Pushpak Bhattacharyya

In this paper, we hypothesize that sarcasm is closely related to sentiment and emotion, and thereby propose a multi-task deep learning framework to solve all these three problems simultaneously in a multi-modal conversational scenario.

Emotion Recognition Multi-Task Learning +3

Can Neural Networks Automatically Score Essay Traits?

no code implementations WS 2020 S Mathias, eep, Pushpak Bhattacharyya

Essay traits are attributes of an essay that can help explain how well written (or badly written) the essay is.

BIG-bench Machine Learning Sentence

Extracting N-ary Cross-sentence Relations using Constrained Subsequence Kernel

no code implementations15 Jun 2020 Sachin Pawar, Pushpak Bhattacharyya, Girish K. Palshikar

Most of the past work in relation extraction deals with relations occurring within a sentence and having only two entity arguments.

Relation Relation Extraction +2

Happy Are Those Who Grade without Seeing: A Multi-Task Learning Approach to Grade Essays Using Gaze Behaviour

1 code implementation Asian Chapter of the Association for Computational Linguistics 2020 Sandeep Mathias, Rudra Murthy, Diptesh Kanojia, Abhijit Mishra, Pushpak Bhattacharyya

To demonstrate the efficacy of this multi-task learning based approach to automatic essay grading, we collect gaze behaviour for 48 essays across 4 essay sets, and learn gaze behaviour for the rest of the essays, numbering over 7000 essays.

Multi-Task Learning Named Entity Recognition (NER) +1

A Deep Learning Approach for Automatic Detection of Fake News

1 code implementation ICON 2019 Tanik Saikh, Arkadipta De, Asif Ekbal, Pushpak Bhattacharyya

We evaluate our techniques on the two recently released datasets, namely FakeNews AMT and Celebrity for fake news detection.

Fake News Detection