no code implementations • MMTLRL (RANLP) 2021 • Loitongbam Sanayai Meetei, Thoudam Doren Singh, Sivaji Bandyopadhyay
The parallel corpus is used to train the English-Hindi Neural Machine Translation (NMT) and an English-Hindi MMT system by incorporating the image feature paired with the corresponding parallel corpus.
no code implementations • MMTLRL (RANLP) 2021 • Salam Michael Singh, Loitongbam Sanayai Meetei, Thoudam Doren Singh, Sivaji Bandyopadhyay
In this work, we utilise the multiple captions from the Multi-30K dataset to increase the lexical diversity aided with the cross-lingual transfer of information among the languages in a multilingual setup.
no code implementations • WMT (EMNLP) 2020 • Sahinur Rahman Laskar, Abdullah Faiz Ur Rahman Khilji, Partha Pakray, Sivaji Bandyopadhyay
We have participated in WMT20 shared task of similar language translation on Hindi-Marathi pair.
no code implementations • WAT 2022 • Sahinur Rahman Laskar, Rahul Singh, Md Faizal Karim, Riyanka Manna, Partha Pakray, Sivaji Bandyopadhyay
Machine translation translates one natural language to another, a well-defined natural language processing task.
no code implementations • GWC 2018 • Anupam Mondal, Dipankar Das, Erik Cambria, Sivaji Bandyopadhyay
Information extraction in the medical domain is laborious and time-consuming due to the insufficient number of domain-specific lexicons and lack of involvement of domain experts such as doctors and medical practitioners.
no code implementations • ICON 2020 • Sainik Mahata, Dipankar Das, Sivaji Bandyopadhyay
In the current work, we present the description of the systems submitted to a machine translation shared task organized by ICON 2020: 17th International Conference on Natural Language Processing.
no code implementations • AACL (WAT) 2020 • Sahinur Rahman Laskar, Abdullah Faiz Ur Rahman Khilji, Partha Pakray, Sivaji Bandyopadhyay
Moreover, the utilization of monolingual data in the pre-training step can improve the performance of the system for low resource language translations.
no code implementations • WAT 2022 • Sahinur Rahman Laskar, Riyanka Manna, Partha Pakray, Sivaji Bandyopadhyay
In the domain of natural language processing, machine translation is a well-defined task where one natural language is automatically translated to another natural language.
no code implementations • WAT 2022 • Sahinur Rahman Laskar, Pankaj Dadure, Riyanka Manna, Partha Pakray, Sivaji Bandyopadhyay
Automatic translation of one natural language to another is a popular task of natural language processing.
no code implementations • ACL (WAT) 2021 • Sahinur Rahman Laskar, Abdullah Faiz Ur Rahman Khilji, Darsh Kaushik, Partha Pakray, Sivaji Bandyopadhyay
Neural machine translation attains a state-of-the-art approach in machine translation, but it requires adequate training data, which is a severe problem for low-resource language pairs translation.
no code implementations • EACL (DravidianLangTech) 2021 • Sainik Mahata, Dipankar Das, Sivaji Bandyopadhyay
In this work, we take up a similar challenge of developing a sentiment analysis model that can work with English-Tamil code-mixed data.
no code implementations • ROCLING 2022 • Prachurya Nath, Prottay Kumar Adhikary, Pankaj Dadure, Partha Pakray, Riyanka Manna, Sivaji Bandyopadhyay
The unavailability of an image caption generation system for the Assamese language is an open problem for AI-NLP researchers, and it’s just an early stage of the research.
no code implementations • ICON 2021 • Salam Michael Singh, Loitongbam Sanayai Meetei, Alok Singh, Thoudam Doren Singh, Sivaji Bandyopadhyay
In recent times, machine translation models can learn to perform implicit bridging between language pairs never seen explicitly during training and showing that transfer learning helps for languages with constrained resources.
no code implementations • ICON 2021 • Alok Singh, Loitongbam Sanayai Meetei, Salam Michael Singh, Thoudam Doren Singh, Sivaji Bandyopadhyay
Describing a video is a challenging yet attractive task since it falls into the intersection of computer vision and natural language generation.
Ranked #1 on Video Captioning on Hindi MSR-VTT
no code implementations • loresmt (AACL) 2020 • Sahinur Rahman Laskar, Abdullah Faiz Ur Rahman Khilji, Partha Pakray, Sivaji Bandyopadhyay
The availability of a parallel corpus in low resource language pairs is one of the challenging tasks in MT.
no code implementations • loresmt (AACL) 2020 • Sahinur Rahman Laskar, Abdullah Faiz Ur Rahman Khilji, Partha Pakray, Sivaji Bandyopadhyay
The corpus preparation is one of the important challenging task for the domain of machine translation especially in low resource language scenarios.
no code implementations • MTSummit 2021 • Sahinur Rahman Laskar, Abdullah Faiz Ur Rahman Khilji Darsh Kaushik, Partha Pakray, Sivaji Bandyopadhyay
In machine translation, corpus preparation is one of the crucial tasks, particularly for lowresource pairs.
no code implementations • GWC 2016 • Anupam Mondal, Dipankar Das, Erik Cambria, Sivaji Bandyopadhyay
In order to overcome the lack of medical corpora, we have developed a WordNet for Medical Events (WME) for identifying medical terms and their sense related information using a seed list.
no code implementations • ICON 2020 • Loitongbam Sanayai Meetei, Thoudam Doren Singh, Sivaji Bandyopadhyay, Mihaela Vela, Josef van Genabith
A Computer Assisted Translation (CAT) tool is used to record the time, keystroke and other indicators to measure PE effort in terms of temporal and technical effort.
no code implementations • WMT (EMNLP) 2020 • Salam Michael Singh, Thoudam Doren Singh, Sivaji Bandyopadhyay
We describe NITS-CNLP’s submission to WMT 2020 unsupervised machine translation shared task for German language (de) to Upper Sorbian (hsb) in a constrained setting i. e, using only the data provided by the organizers.
no code implementations • WMT (EMNLP) 2021 • Sahinur Rahman Laskar, Bishwaraj Paul, Prottay Kumar Adhikary, Partha Pakray, Sivaji Bandyopadhyay
The neural machine translation approach has gained popularity in machine translation because of its context analysing ability and its handling of long-term dependency issues.
no code implementations • ICON 2021 • Loitongbam Sanayai Meetei, Laishram Rahul, Alok Singh, Salam Michael Singh, Thoudam Doren Singh, Sivaji Bandyopadhyay
Based on this dataset, a benchmark evaluation is reported for the Manipuri-English Speech-to-Text translation using two approaches: 1) a pipeline model consisting of ASR (Automatic Speech Recognition) and Machine translation, and 2) an end-to-end Speech-to-Text translation.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +4
no code implementations • Multimedia Tools and Applications 2021 • Alok Singh, Thoudam Doren Singh, Sivaji Bandyopadhyay
The model is tested over Hindi visual genome dataset to validate the proposed approach’s performance and cross-verification is carried out for English captions with Flickr dataset.
no code implementations • journal 2021 • Alok Singh, · Thoudam Doren Singh, Sivaji Bandyopadhyay
In recent times, active research is going on for bridging the gap between computer vision and natural language.
Ranked #2 on Video Captioning on Hindi MSR-VTT
no code implementations • 30 Nov 2020 • Alok Singh, Thoudam Doren Singh, Sivaji Bandyopadhyay
In this work, we report a comprehensive survey on the phases of video description approaches, the dataset for video description, evaluation metrics, open competitions for motivating the research on the video description, open challenges in this field, and future research directions.
1 code implementation • 20 Oct 2020 • Sainik Kumar Mahata, Dipankar Das, Sivaji Bandyopadhyay
Sentiment analysis has been an active area of research in the past two decades and recently, with the advent of social media, there has been an increasing demand for sentiment analysis on social media texts.
no code implementations • 31 Aug 2020 • Somnath Banerjee, Sudip Kumar Naskar, Paolo Rosso, Sivaji Bandyopadhyay
Overall, the stacking approach produces the best results for fine-grained classification and achieves 87. 79% of accuracy.
no code implementations • ICON 2019 • Tathagata Raha, Sainik Kumar Mahata, Dipankar Das, Sivaji Bandyopadhyay
The proposed system is a modular approach that starts by tagging individual tokens with their respective languages and then passes them to different POS taggers, designed for different languages (English and Bengali, in our case).
no code implementations • 28 Jul 2020 • Sainik Kumar Mahata, Amrita Chandra, Dipankar Das, Sivaji Bandyopadhyay
The preparation of raw parallel corpus, sentiment analysis of the sentences and the training of a Character Based Neural Machine Translation model using the same has been discussed extensively in this paper.
2 code implementations • 20 Jun 2020 • Thoudam Doren Singh, Abdullah Faiz Ur Rahman Khilji, Divyansha, Apoorva Vikram Singh, Surmila Thokchom, Sivaji Bandyopadhyay
Experimental methods state that our model has achieved accuracy surpassing mixture of other techniques and adaptive command line interface mechanism as acclaimed in the past.
no code implementations • 7 Jun 2020 • Alok Singh, Thoudam Doren Singh, Sivaji Bandyopadhyay
Video captioning is process of summarising the content, event and action of the video into a short textual form which can be helpful in many research areas such as video guided machine translation, video sentiment analysis and providing aid to needy individual.
Ranked #10 on Video Captioning on VATEX
no code implementations • 9 Nov 2019 • Sainik Kumar Mahata, Soumil Mandal, Dipankar Das, Sivaji Bandyopadhyay
The use of multilingualism in the new generation is widespread in the form of code-mixed data on social media, and therefore a robust translation system is required for catering to the monolingual users, as well as for easier comprehension by language processing models.
no code implementations • WS 2019 • Sainik Kumar Mahata, Avishek Garain, Adityar Rayala, Dipankar Das, Sivaji Bandyopadhyay
In the current work, we present a description of the system submitted to WMT 2019 News Translation Shared task.
no code implementations • WS 2018 • Sainik Kumar Mahata, Dipankar Das, Sivaji Bandyopadhyay
In the current work, we present a description of the system submitted to WMT 2018 News Translation Shared task.
no code implementations • 12 Dec 2018 • Sainik Kumar Mahata, Soumil Mandal, Dipankar Das, Sivaji Bandyopadhyay
All of the systems use English-Hindi and English-Bengali language pairs containing simple sentences as well as sentences of other complexity.
no code implementations • 23 Jan 2014 • Tanmoy Chakraborty, Dipankar Das, Sivaji Bandyopadhyay
As a by-product of this experiment, we have started developing a standard lexicon in Bengali that serves as a productive Bengali linguistic thesaurus.