Search Results for author:
Found 369 papers, 39 papers with code
pyiwn: A Python based API to access Indian Language WordNets
Indian language WordNets have their individual web-based browsing interfaces along with a common interface for IndoWordNet.
A picture is worth a thousand words: Using OpenClipArt library for enriching IndoWordNet
Our contribution is three fold: (1) We develop a system, which, given a synset in English, finds an appropriate image for the synset.
Sophisticated Lexical Databases - Simplified Usage: Mobile Applications and Browser Plugins For Wordnets
India is a country with 22 officially recognized languages and 17 of these have WordNets, a crucial resource.
IndoWordNet::Similarity- Computing Semantic Similarity and Relatedness using IndoWordNet
This tool, web interface and the API are made available for the research purpose.
Detecting Most Frequent Sense using Word Embeddings and BabelNet
In this paper, we present our work on Most Frequent Sense (MFS) detection using Word Embeddings and BabelNet features.
Converting Sentiment Annotated Data to Emotion Annotated Data
Given a sentence and its sentiment information, recognize the best possible emotion for it.
A Multi-task Model for Multilingual Trigger Detection and Classification
In this paper we present a deep multi-task learning framework for multilingual event and argument trigger detection and classification.
Multi-linguality helps: Event-Argument Extraction for Disaster Domain in Cross-lingual and Multi-lingual setting
Extracting related arguments like Time, Place, Casualties, etc., provides a complete picture of the disaster event.
A Deep Ensemble Framework for Fake News Detection and Multi-Class Classification of Short Political Statements
Fake news, rumor, incorrect information, and misinformation detection are nowadays crucial issues as these might have serious consequences for our social fabrics.
“So You Think You’re Funny?”: Rating the Humour Quotient in Standup Comedy
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).
Modelling Source- and Target- Language Syntactic Information as Conditional Context in Interactive Neural Machine Translation
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).
Synthesizing Audio for Hindi WordNet
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.
Hindi Wordnet for Language Teaching: Experiences and Lessons Learnt
This aid is based on modern pedagogical axioms and is aligned to the learning objectives of the syllabi of the school education in India.
Multiple Pivot Languages and Strategic Decoder Initialization Helps Neural Machine Translation
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.
Novelty Detection: A Perspective from Natural Language Processing
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.
Team IITP-AINLPML at WASSA 2022: Empathy Detection, Emotion Classification and Personality Detection
Computational comprehension and identifying emotional components in language have been critical in enhancing human-computer connection in recent years.
BERT based Adverse Drug Effect Tweet Classification
This paper describes models developed for the Social Media Mining for Health (SMM4H) 2021 shared tasks.
Language Model Pretraining and Transfer Learning for Very Low Resource Languages
This paper describes our submission for the shared task on Unsupervised MT and Very Low Resource Supervised MT at WMT 2021.
Pivot Based Transfer Learning for Neural Machine Translation: CFILT IITB @ WMT 2021 Triangular MT
Such a large amount of parallel corpus is majorly available for language pairs which include English and not for non-English language pairs.
An Iterative Approach for Unsupervised Most Frequent Sense Detection using WordNet and Word Embeddings
Given a word, what is the most frequent sense in which it occurs in a given corpus?
Annotated Corpus of Tweets in English from Various Domains for Emotion Detection
We propose a Hierarchical Attention-based deep neural network for Emotion Detection (HAtED).
D-Coref: A Fast and Lightweight Coreference Resolution Model using DistilBERT
Smart devices are often deployed in some edge-devices, which require quality solutions in limited amount of memory usage.
A Multi-modal Personality Prediction System
Automatic prediction of personality traits has many real-life applications, e. g., in forensics, recommender systems, personalized services etc..
Personality Trait Recognition by Face
Recommendation Systems
Mapping it differently: A solution to the linking challenges
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.
High, Medium or Low? Detecting Intensity Variation Among polar synonyms in WordNet
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.
Samāsa-Kartā: An Online Tool for Producing Compound Words using IndoWordNet
The meaning of this word is derived from each of the individual words of the compound.
IndoWordNet Conversion to Web Ontology Language (OWL)
In this paper, we present a data representation of IndoWordNet in Web Ontology Language (OWL).
IITP-MT at CALCS2021: English to Hinglish Neural Machine Translation using Unsupervised Synthetic Code-Mixed Parallel Corpus
We submit a neural machine translation (NMT) system which is trained on the synthetic code-mixed (cm) English-Hinglish parallel corpus.
A Shoulder to Cry on: Towards A Motivational Virtual Assistant for Assuaging Mental Agony
Mental Health Disorders continue plaguing humans worldwide.
Evaluating the Performance of Back-translation for Low Resource English-Marathi Language Pair: CFILT-IITBombay @ LoResMT 2021
In this paper, we discuss the details of the various Machine Translation (MT) systems that we have submitted for the English-Marathi LoResMT task.
IIITBH-IITP@CL-SciSumm20, CL-LaySumm20, LongSumm20
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.
IITP-AI-NLP-ML@ CL-SciSumm 2020, CL-LaySumm 2020, LongSumm 2020
The publication rate of scientific literature increases rapidly, which poses a challenge for researchers to keep themselves updated with new state-of-the-art.
Knowledge Graph and Deep Neural Network for Extractive Text Summarization by Utilizing Triples
In our research work, we represent the content of the sentence in graphical form after extracting triples from the sentences.
Language Relatedness and Lexical Closeness can help Improve Multilingual NMT: IITBombay@MultiIndicNMT WAT2021
Multilingual Neural Machine Translation has achieved remarkable performance by training a single translation model for multiple languages.
Multilingual Machine Translation Systems at WAT 2021: One-to-Many and Many-to-One Transformer based NMT
In this paper, we present the details of the systems that we have submitted for the WAT 2021 MultiIndicMT: An Indic Language Multilingual Task.
IITP-MT at WAT2021: Indic-English Multilingual Neural Machine Translation using Romanized Vocabulary
This paper describes the systems submitted to WAT 2021 MultiIndicMT shared task by IITP-MT team.
CFILT IIT Bombay@LT-EDI-EACL2021: Hope Speech Detection for Equality, Diversity, and Inclusion using Multilingual Representation fromTransformers
This paper presents our system for the shared task Hope Speech Detection for Equality, Diversity, and Inclusion at LT-EDI, EACL 2021.
SEPRG: Sentiment aware Emotion controlled Personalized Response Generation
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.
Investigating Active Learning in Interactive Neural Machine Translation
It also improves the present state-of-the-art by 0. 35 and 0. 12 BLEU points for German-English and Spanish-English and respectively.
EM-PERSONA: EMotion-assisted Deep Neural Framework for PERSONAlity Subtyping from Suicide Notes
We address the challenging task of personality subtyping from suicide notes.
HindiMD: A Multi-domain Corpora for Low-resource Sentiment Analysis
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.
Retrofitting of Pre-trained Emotion Words with VAD-dimensions and the Plutchik Emotions
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 Enriched Retrofitted Word Embeddings
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.
Zero-shot Disfluency Detection for Indian Languages
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
PoliSe: Reinforcing Politeness Using User Sentiment for Customer Care Response Generation
The interaction between a consumer and the customer service representative greatly contributes to the overall customer experience.
A Sentiment and Emotion Aware Multimodal Multiparty Humor Recognition in Multilingual Conversational Setting
We design a multitasking framework wherein we first propose a Context Transformer to capture the deep contextual relationships with the input utterances.
COMMA-DEER: COmmon-sense Aware Multimodal Multitask Approach for Detection of Emotion and Emotional Reasoning in Conversations
We present and discuss a novel task of detecting emotional reasoning (ER) and accompanying emotions in conversations.
EduMT: Developing Machine Translation System for Educational Content in Indian Languages
In this paper, we explore various approaches to build Hindi to Bengali Neural Machine Translation (NMT) systems for the educational domain.
A Scaled Encoder Decoder Network for Image Captioning in Hindi
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).
Introduction to ProverbNet: An Online Multilingual Database of Proverbs and Comprehensive Metadata
Proverbs are unique linguistic expressions used by humans in the process of communication.
Wikipedia Current Events Summarization using Particle Swarm Optimization
The obtained results show the efficacy of the proposed methodology over the state-of-the-art methods.
Product Description and QA Assisted Self-Supervised Opinion Summarization
For evaluation, due to the unavailability of test sets with additional sources, we extend the Amazon, Oposum+, and Flipkart test sets and leverage ChatGPT to annotate summaries.
A Morphology-Based Investigation of Positional Encodings
How does the importance of positional encoding in pre-trained language models (PLMs) vary across languages with different morphological complexity?
IndiBias: A Benchmark Dataset to Measure Social Biases in Language Models for Indian Context
We filter and translate the existing CrowS-Pairs dataset to create a benchmark dataset suited to the Indian context in Hindi language.
Do Not Worry if You Do Not Have Data: Building Pretrained Language Models Using Translationese
In this paper, we explore the utility of Translationese as synthetic data created using machine translation for pre-training language models (LMs).
Material Microstructure Design Using VAE-Regression with Multimodal Prior
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.
Leveraging Domain Knowledge for Efficient Reward Modelling in RLHF: A Case-Study in E-Commerce Opinion Summarization
While this strategy has proven effective, the training methodology requires a lot of human preference annotation (usually in the order of tens of thousands) to train $\varphi$.
Transformers are Expressive, But Are They Expressive Enough for Regression?
Expressivity of a neural network is the class of functions it can approximate.
One Prompt To Rule Them All: LLMs for Opinion Summary Evaluation
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.
Meme-ingful Analysis: Enhanced Understanding of Cyberbullying in Memes Through Multimodal Explanations
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
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.
PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics Capabilities
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.
Yes, this is what I was looking for! Towards Multi-modal Medical Consultation Concern Summary Generation
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.
APE-then-QE: Correcting then Filtering Pseudo Parallel Corpora for MT Training Data Creation
We propose a repair-filter-use methodology that uses an APE system to correct errors on the target side of the MT training data.
IndicIRSuite: Multilingual Dataset and Neural Information Models for Indian Languages
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.
Reinforcement Replaces Supervision: Query focused Summarization using Deep Reinforcement Learning
Query-focused Summarization (QfS) deals with systems that generate summaries from document(s) based on a query.
Retrofitting Light-weight Language Models for Emotions using Supervised Contrastive Learning
We present a novel retrofitting method to induce emotion aspects into pre-trained language models (PLMs) such as BERT and RoBERTa.
DISCO: A Large Scale Human Annotated Corpus for Disfluency Correction in Indo-European Languages
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
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).
Experience and Evidence are the eyes of an excellent summarizer! Towards Knowledge Infused Multi-modal Clinical Conversation Summarization
We propose a knowledge-infused, multi-modal, multi-tasking medical domain identification and clinical conversation summary generation (MM-CliConSummation) framework.
Hi Model, generating 'nice' instead of 'good' is not as bad as generating 'rice'! Towards Context and Semantic Infused Dialogue Generation Loss Function and Evaluation Metric
These lexical-based metrics have the following key limitations: (a) word-to-word matching without semantic consideration: It assigns the same credit for failure to generate 'nice' and 'rice' for 'good'.
"Beware of deception": Detecting Half-Truth and Debunking it through Controlled Claim Editing
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
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.
"Kurosawa": A Script Writer's Assistant
We fine-tune GPT-3 with the above datasets to generate plots and scenes.
Decision Knowledge Graphs: Construction of and Usage in Question Answering for Clinical Practice Guidelines
In this paper, we present a Decision Knowledge Graph (DKG) representation to store CPGs and to perform question-answering on CPGs.
"We care": Improving Code Mixed Speech Emotion Recognition in Customer-Care Conversations
Emotion recognition is essential in building robust conversational agents in domains such as law, healthcare, education, and customer support.
Adversarial Training For Low-Resource Disfluency Correction
Disfluencies commonly occur in conversational speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
"A Little is Enough": Few-Shot Quality Estimation based Corpus Filtering improves Machine Translation
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.
"Let's not Quote out of Context": Unified Vision-Language Pretraining for Context Assisted Image Captioning
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.
A Match Made in Heaven: A Multi-task Framework for Hyperbole and Metaphor Detection
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.
DisfluencyFixer: A tool to enhance Language Learning through Speech To Speech Disfluency Correction
Conversational speech often consists of deviations from the speech plan, producing disfluent utterances that affect downstream NLP tasks.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
VAKTA-SETU: A Speech-to-Speech Machine Translation Service in Select Indic Languages
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
We aim to investigate whether UNMT approaches with self-supervised pre-training are robust to word-order divergence between language pairs.
Improving Machine Translation with Phrase Pair Injection and Corpus Filtering
In this paper, we show that the combination of Phrase Pair Injection and Corpus Filtering boosts the performance of Neural Machine Translation (NMT) systems.
There is No Big Brother or Small Brother: Knowledge Infusion in Language Models for Link Prediction and Question Answering
In this context, we infuse knowledge in large and small language models and study their performance, and find the performance to be similar.
Ranked #1 on
Question Answering
on AviationQA
Detecting Unintended Social Bias in Toxic Language Datasets
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
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.
A Multimodal Corpus for Emotion Recognition in Sarcasm
Detecting the emotion behind a sarcastic expression is non-trivial yet an important task.
Ranked #1 on
Sarcasm Detection
on MUStARD++
Knowledge Graph - Deep Learning: A Case Study in Question Answering in Aviation Safety Domain
We construct a Knowledge Graph from Aircraft Accident reports and contribute this resource to the community of researchers.
Hollywood Identity Bias Dataset: A Context Oriented Bias Analysis of Movie Dialogues
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.
EmoInHindi: A Multi-label Emotion and Intensity Annotated Dataset in Hindi for Emotion Recognition in Dialogues
The long-standing goal of Artificial Intelligence (AI) has been to create human-like conversational systems.
Am I No Good? Towards Detecting Perceived Burdensomeness and Thwarted Belongingness from Suicide Notes
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
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.
Ranked #1 on
Named Entity Recognition (NER)
on HiNER-original
Indian Language Wordnets and their Linkages with Princeton WordNet
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
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.
Semi-automatic WordNet Linking using Word Embeddings
Thus techniques that can aid the experts are desirable.
Utilizing Wordnets for Cognate Detection among Indian Languages
Automatic Cognate Detection (ACD) is a challenging task which has been utilized to help NLP applications like Machine Translation, Information Retrieval and Computational Phylogenetics.
"A Passage to India": Pre-trained Word Embeddings for Indian Languages
In this paper, we use various existing approaches to create multiple word embeddings for 14 Indian languages.
A Survey on Using Gaze Behaviour for Natural Language Processing
Gaze behaviour has been used as a way to gather cognitive information for a number of years.
Challenge Dataset of Cognates and False Friend Pairs from Indian Languages
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.
Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource Languages
We, then, evaluate the impact of our cognate detection mechanism on neural machine translation (NMT), as a downstream task.
Cross-Lingual Information Retrieval
Cross-Lingual Word Embeddings
+5
Cognition-aware Cognate Detection
We collect gaze behaviour data for a small sample of cognates and show that extracted cognitive features help the task of cognate detection.
Natural Answer Generation: From Factoid Answer to Full-length Answer using Grammar Correction
A transformer-based Grammar Error Correction model GECToR (2020), is used as a post-processing step for better fluency.
Tapping BERT for Preposition Sense Disambiguation
In this paper, we propose a novel methodology for preposition sense disambiguation (PSD), which does not use any linguistic tools.
"So You Think You're Funny?": Rating the Humour Quotient in Standup Comedy
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
This dataset creates a new avenue of carrying out research on COVID-19 by providing a benchmark dataset and a baseline model.
Role of Language Relatedness in Multilingual Fine-tuning of Language Models: A Case Study in Indo-Aryan Languages
We hypothesize and validate that multilingual fine-tuning of pre-trained language models can yield better performance on downstream NLP applications, compared to models fine-tuned on individual languages.
Multiple Choice Question Answering (MCQA)
Natural Language Inference
+3
M2H2: A Multimodal Multiparty Hindi Dataset For Humor Recognition in Conversations
We propose several strong multimodal baselines and show the importance of contextual and multimodal information for humor recognition in conversations.
Global Object Proposals for Improving Multi-Sentence Video Descriptions
Recently, many works are proposed on the generation of multi-sentence video descriptions.
Ranked #2 on
Dense Video Captioning
on ActivityNet Captions
Crosslingual Embeddings are Essential in UNMT for Distant Languages: An English to IndoAryan Case Study
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.
Towards Sentiment and Emotion aided Multi-modal Speech Act Classification in Twitter
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.
How low is too low? A monolingual take on lemmatisation in Indian languages
Lemmatization aims to reduce the sparse data problem by relating the inflected forms of a word to its dictionary form.
Semantic Extractor-Paraphraser based Abstractive Summarization
The anthology of spoken languages today is inundated with textual information, necessitating the development of automatic summarization models.
Disfluency Correction using Unsupervised and Semi-supervised Learning
Spoken language is different from the written language in its style and structure.
Modelling Context Emotions using Multi-task Learning for Emotion Controlled Dialog Generation
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.
Techniques for Jointly Extracting Entities and Relations: A Survey
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.
Knowledge-based Extraction of Cause-Effect Relations from Biomedical Text
We propose a knowledge-based approach for extraction of Cause-Effect (CE) relations from biomedical text.
Cognitively Aided Zero-Shot Automatic Essay Grading
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.
Many Hands Make Light Work: Using Essay Traits to Automatically Score Essays
To find out which traits work best for different types of essays, we conduct ablation tests for each of the essay traits.
Ranked #4 on
Automated Essay Scoring
on ASAP
Can Taxonomy Help? Improving Semantic Question Matching using Question Taxonomy
In this paper, we propose a hybrid technique for semantic question matching.
Divide and Conquer: An Ensemble Approach for Hostile Post Detection in Hindi
This paper present our system for Shared Task at Constraint2021 on "Hostile Post Detection in Hindi".
EmotionGIF-IITP-AINLPML: Ensemble-based Automated Deep Neural System for predicting category(ies) of a GIF response
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 Unified Framework for Multilingual and Code-Mixed Visual Question Answering
We propose a robust tech- nique capable of handling the multilingual and code-mixed question to provide the answer against the visual information (image).
A Retrofitting Model for Incorporating Semantic Relations into Word Embeddings
We present a novel retrofitting model that can leverage relational knowledge available in a knowledge resource to improve word embeddings.
Unsupervised Aspect-Level Sentiment Controllable Style Transfer
Unsupervised style transfer in text has previously been explored through the sentiment transfer task.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+3
All-in-One: A Deep Attentive Multi-task Learning Framework for Humour, Sarcasm, Offensive, Motivation, and Sentiment on Memes
The main motivation of iTRM is to learn the relationship between the tasks to realize how they help each other.
Filtering Back-Translated Data in Unsupervised Neural Machine Translation
Our approach gives more weight to good pseudo parallel sentence pairs in the back-translation phase.
MEISD: A Multimodal Multi-Label Emotion, Intensity and Sentiment Dialogue Dataset for Emotion Recognition and Sentiment Analysis in Conversations
Multi-label emotion detection in conversations is a significant task that provides the ability to the system to understand the various emotions of the users interacting.
Analysing cross-lingual transfer in lemmatisation for Indian languages
Lemmatization aims to reduce the sparse data problem by relating the inflected forms of a word to its dictionary form.
IITP-AINLPML at SemEval-2020 Task 12: Offensive Tweet Identification and Target Categorization in a Multitask Environment
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.
EL-BERT at SemEval-2020 Task 10: A Multi-Embedding Ensemble Based Approach for Emphasis Selection in Visual Media
Emphasis selection is the task of choosing candidate words for emphasis, it helps in automatically designing posters and other media contents with written text.
Looking inside Noun Compounds: Unsupervised Prepositional and Free Paraphrasing
Our approach uses templates to prepare the input sequence for the language model.
A Semi-supervised Approach to Generate the Code-Mixed Text using Pre-trained Encoder and Transfer Learning
Code-mixing, the interleaving of two or more languages within a sentence or discourse is ubiquitous in multilingual societies.
Assessing the Severity of Health States based on Social Media Posts
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.
Tweet to News Conversion: An Investigation into Unsupervised Controllable Text Generation
The second system stitches together the outputs from the first system to form a coherent news paragraph.
Can Neural Networks Automatically Score Essay Traits?
Essay traits are attributes of an essay that can help explain how well written (or badly written) the essay is.
Extracting Message Sequence Charts from Hindi Narrative Text
In this paper, we propose the use of Message Sequence Charts (MSC) as a representation for visualizing narrative text in Hindi.
Generating Fluent Translations from Disfluent Text Without Access to Fluent References: IIT Bombay@IWSLT2020
We also make use of additional fluent text in the target language to help generate fluent translations.
Sentiment and Emotion help Sarcasm? A Multi-task Learning Framework for Multi-Modal Sarcasm, Sentiment and Emotion Analysis
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.
Towards Emotion-aided Multi-modal Dialogue Act Classification
In this work, we address the role of \textit{both} multi-modality and emotion recognition (ER) in DAC.
Extracting N-ary Cross-sentence Relations using Constrained Subsequence Kernel
Most of the past work in relation extraction deals with relations occurring within a sentence and having only two entity arguments.
Happy Are Those Who Grade without Seeing: A Multi-Task Learning Approach to Grade Essays Using Gaze Behaviour
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.
A Deep Learning Approach for Automatic Detection of Fake News
We evaluate our techniques on the two recently released datasets, namely FakeNews AMT and Celebrity for fake news detection.
Part-of-Speech Annotation Challenges in Marathi
Part of Speech (POS) annotation is a significant challenge in natural language processing.
A Platform for Event Extraction in Hindi
In this paper, we present an Event Extraction framework for Hindi language by creating an annotated resource for benchmarking, and then developing deep learning based models to set as the baselines.
CEASE, a Corpus of Emotion Annotated Suicide notes in English
In this paper, we create a fine-grained emotion annotated corpus (CEASE) of suicide notes in English and develop various deep learning models to perform emotion detection on the curated dataset.
Incorporating Politeness across Languages in Customer Care Responses: Towards building a Multi-lingual Empathetic Dialogue Agent
Our system is competent in generating responses in different languages (here, English and Hindi) depending on the customer{'}s preference and also is able to converse with humans in an empathetic manner to ensure customer satisfaction and retention.
ScholarlyRead: A New Dataset for Scientific Article Reading Comprehension
We present ScholarlyRead, span-of-word-based scholarly articles{'} Reading Comprehension (RC) dataset with approximately 10K manually checked passage-question-answer instances.
Recommendation Chart of Domains for Cross-Domain Sentiment Analysis: Findings of A 20 Domain Study
Cross-domain sentiment analysis (CDSA) helps to address the problem of data scarcity in scenarios where labelled data for a domain (known as the target domain) is unavailable or insufficient.
Multi-domain Tweet Corpora for Sentiment Analysis: Resource Creation and Evaluation
Due to the phenomenal growth of online content in recent time, sentiment analysis has attracted attention of the researchers and developers.
``A Passage to India'': Pre-trained Word Embeddings for Indian Languages
In this paper, we use various existing approaches to create multiple word embeddings for 14 Indian languages.
Recommendation Chart of Domains for Cross-Domain Sentiment Analysis:Findings of A 20 Domain Study
Cross-domain sentiment analysis (CDSA) helps to address the problem of data scarcity in scenarios where labelled data for a domain (known as the target domain) is unavailable or insufficient.
Reinforced Multi-task Approach for Multi-hop Question Generation
Question generation (QG) attempts to solve the inverse of question answering (QA) problem by generating a natural language question given a document and an answer.
Utilizing Language Relatedness to improve Machine Translation: A Case Study on Languages of the Indian Subcontinent
To the best of our knowledge, this is the first large-scale study specifically devoted to utilizing language relatedness to improve translation between related languages.
Related Tasks can Share! A Multi-task Framework for Affective language
Expressing the polarity of sentiment as 'positive' and 'negative' usually have limited scope compared with the intensity/degree of polarity.
A Deep Neural Framework for Contextual Affect Detection
A short and simple text carrying no emotion can represent some strong emotions when reading along with its context, i. e., the same sentence can express extreme anger as well as happiness depending on its context.
Machine Translation Evaluation using Bi-directional Entailment
We apply our evaluation metric on WMT'14 and WMT'17 dataset to evaluate systems participating in the translation task and find that our metric has a better correlation with the human annotated score compared to the other traditional metrics at system level.
Context-aware Interactive Attention for Multi-modal Sentiment and Emotion Analysis
In this paper, we introduce a recurrent neural network based approach for the multi-modal sentiment and emotion analysis.
Scrambled Translation Problem: A Problem of Denoising UNMT
We hypothesise that the reason behind \textit{scrambled translation problem} is 'shuffling noise' which is introduced in every input sentence as a denoising strategy.
Tale of tails using rule augmented sequence labeling for event extraction
The problem of event extraction is a relatively difficult task for low resource languages due to the non-availability of sufficient annotated data.
Utilizing Monolingual Data in NMT for Similar Languages: Submission to Similar Language Translation Task
This paper describes our submission to Shared Task on Similar Language Translation in Fourth Conference on Machine Translation (WMT 2019).
IITP-MT System for Gujarati-English News Translation Task at WMT 2019
We describe our submission to WMT 2019 News translation shared task for Gujarati-English language pair.
Parallel Corpus Filtering Based on Fuzzy String Matching
Based on the scores, we sub-sample two sets (having 1 million and 5 millions English tokens) of parallel sentences from each parallel corpus, and train SMT systems for development purpose only.
DeepSentiPeer: Harnessing Sentiment in Review Texts to Recommend Peer Review Decisions
However, the peer review texts, which contains rich sentiment information of the reviewer, reflecting his/her overall attitude towards the research in the paper, could be a valuable entity to predict the acceptance or rejection of the manuscript under consideration.
A Unified Multi-task Adversarial Learning Framework for Pharmacovigilance Mining
The mining of adverse drug reaction (ADR) has a crucial role in the pharmacovigilance.
Ordinal and Attribute Aware Response Generation in a Multimodal Dialogue System
Multimodal dialogue systems have opened new frontiers in the traditional goal-oriented dialogue systems.
Extraction of Message Sequence Charts from Narrative History Text
In this paper, we advocate the use of Message Sequence Chart (MSC) as a knowledge representation to capture and visualize multi-actor interactions and their temporal ordering.
Extraction of Message Sequence Charts from Software Use-Case Descriptions
We apply this tool to extract MSCs from several real-life software use-case descriptions and show that it performs better than the existing techniques.
Courteously Yours: Inducing courteous behavior in Customer Care responses using Reinforced Pointer Generator Network
We use real interactions on Twitter between customer care professionals and aggrieved customers to create a large conversational dataset having both forms of agent responses: {`}generic{'} and {`}courteous{'}.
``When Numbers Matter!'': Detecting Sarcasm in Numerical Portions of Text
Initially, to get an insight into the problem, we implement a rule-based and a statistical machine learning-based (ML) classifier.
Multi-task Learning for Multi-modal Emotion Recognition and Sentiment Analysis
In this paper, we present a deep multi-task learning framework that jointly performs sentiment and emotion analysis both.
Language-Agnostic Model for Aspect-Based Sentiment Analysis
In this paper, we propose a language-agnostic deep neural network architecture for aspect-based sentiment analysis.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+3
Relation extraction between the clinical entities based on the shortest dependency path based LSTM
In this paper, we present an efficient relation extraction system based on the shortest dependency path (SDP) generated from the dependency parsed tree of the sentence.
A Deep Ensemble Framework for Fake News Detection and Classification
Fake news, rumor, incorrect information, and misinformation detection are nowadays crucial issues as these might have serious consequences for our social fabrics.
Helping each Other: A Framework for Customer-to-Customer Suggestion Mining using a Semi-supervised Deep Neural Network
We evaluate the performance of our proposed model on a benchmark customer review dataset, comprising of the reviews of Hotel and Electronics domains.
Addressing word-order Divergence in Multilingual Neural Machine Translation for extremely Low Resource Languages
To bridge this divergence, We propose to pre-order the assisting language sentence to match the word order of the source language and train the parent model.
Eyes are the Windows to the Soul: Predicting the Rating of Text Quality Using Gaze Behaviour
Such subjective aspects are better handled using cognitive information.
Is your Statement Purposeless? Predicting Computer Science Graduation Admission Acceptance based on Statement Of Purpose
We present a quantitative, data-driven machine learning approach to mitigate the problem of unpredictability of Computer Science Graduate School Admissions.
Contextual Inter-modal Attention for Multi-modal Sentiment Analysis
We evaluate our proposed approach on two multi-modal sentiment analysis benchmark datasets, viz.
Ranked #6 on
Multimodal Sentiment Analysis
on MOSI
Uncovering Code-Mixed Challenges: A Framework for Linguistically Driven Question Generation and Neural Based Question Answering
In this paper, we propose a linguistically motivated technique for code-mixed question generation (CMQG) and a neural network based architecture for code-mixed question answering (CMQA).
Combining Graph-based Dependency Features with Convolutional Neural Network for Answer Triggering
Answer triggering is the task of selecting the best-suited answer for a given question from a set of candidate answers if exists.
A Multi-task Ensemble Framework for Emotion, Sentiment and Intensity Prediction
In this paper, through multi-task ensemble framework we address three problems of emotion and sentiment analysis i. e. "emotion classification & intensity", "valence, arousal & dominance for emotion" and "valence & arousal} for sentiment".
Treat us like the sequences we are: Prepositional Paraphrasing of Noun Compounds using LSTM
It has been observed that uncovering the preposition is a significant step towards uncovering the predicate.
Novelty Goes Deep. A Deep Neural Solution To Document Level Novelty Detection
The proposed method outperforms the existing state-of-the-art on a document-level novelty detection dataset by a margin of ∼5{\%} in terms of accuracy.
Leveraging Medical Sentiment to Understand Patients Health on Social Media
A large percentage of this population is actively engaged in health social networks to share health-related information.
Feature Assisted bi-directional LSTM Model for Protein-Protein Interaction Identification from Biomedical Texts
In this paper, we present a novel method based on deep bidirectional long short-term memory (B-LSTM) technique that exploits word sequences and dependency path related information to identify PPI information from text.
Thank ``Goodness''! A Way to Measure Style in Student Essays
Essays have two major components for scoring - content and style.
Identification of Alias Links among Participants in Narratives
Identification of distinct and independent participants (entities of interest) in a narrative is an important task for many NLP applications.
Identifying Transferable Information Across Domains for Cross-domain Sentiment Classification
In this paper, we propose that words that do not change their polarity and significance represent the transferable (usable) information across domains for cross-domain sentiment classification.
Judicious Selection of Training Data in Assisting Language for Multilingual Neural NER
Multilingual learning for Neural Named Entity Recognition (NNER) involves jointly training a neural network for multiple languages.
Multi-Task Learning Framework for Mining Crowd Intelligence towards Clinical Treatment
In this paper, we adopt a novel adversarial learning approach for our multi-task learning framework to learn the sentiment{'}s strengths expressed in a medical blog.
Solving Data Sparsity for Aspect Based Sentiment Analysis Using Cross-Linguality and Multi-Linguality
Efficient word representations play an important role in solving various problems related to Natural Language Processing (NLP), data mining, text mining etc.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+2
