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Found 36 papers, 2 papers with code
Hindi-Marathi Cross Lingual Model
We have participated in WMT20 shared task of similar language translation on Hindi-Marathi pair.
Zero-Shot Neural Machine Translation: Russian-Hindi @LoResMT 2020
The availability of a parallel corpus in low resource language pairs is one of the challenging tasks in MT.
EnAsCorp1.0: English-Assamese Corpus
The corpus preparation is one of the important challenging task for the domain of machine translation especially in low resource language scenarios.
JUNLP@ICON2020: Low Resourced Machine Translation for Indic Languages
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.
Investigation of English to Hindi Multimodal Neural Machine Translation using Transliteration-based Phrase Pairs Augmentation
Machine translation translates one natural language to another, a well-defined natural language processing task.
WME 3.0: An Enhanced and Validated Lexicon of Medical Concepts
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.
The NITS-CNLP System for the Unsupervised MT Task at WMT 2020
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.
Multiple Captions Embellished Multilingual Multi-Modal Neural Machine Translation
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.
Low Resource Multimodal Neural Machine Translation of English-Hindi in News Domain
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.
Neural Machine Translation for Tamil–Telugu Pair
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.
Investigation of Multilingual Neural Machine Translation for Indian Languages
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.
English to Bengali Multimodal Neural Machine Translation using Transliteration-based Phrase Pairs Augmentation
Automatic translation of one natural language to another is a popular task of natural language processing.
Sentiment Classification of Code-Mixed Tweets using Bi-Directional RNN and Language Tags
In this work, we take up a similar challenge of developing a sentiment analysis model that can work with English-Tamil code-mixed data.
Image Caption Generation for Low-Resource Assamese Language
The unavailability of an image caption generation system for the Assamese language is an open problem for AI-NLP researchers, and it’s just an early stage of the research.
An Experiment on Speech-to-Text Translation Systems for Manipuri to English on Low Resource Setting
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
On the Transferability of Massively Multilingual Pretrained Models in the Pretext of the Indo-Aryan and Tibeto-Burman Languages
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.
An Efficient Keyframes Selection Based Framework for Video Captioning
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
Improved English to Hindi Multimodal Neural Machine Translation
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.
EnKhCorp1.0: An English–Khasi Corpus
In machine translation, corpus preparation is one of the crucial tasks, particularly for lowresource pairs.
WME: Sense, Polarity and Affinity based Concept Resource for Medical Events
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.
English to Manipuri and Mizo Post-Editing Effort and its Impact on Low Resource Machine Translation
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.
Multimodal Neural Machine Translation for English to Hindi
Moreover, the utilization of monolingual data in the pre-training step can improve the performance of the system for low resource language translations.
An encoder-decoder based framework for hindi image caption generation
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.
Attention based video captioning framework for Hindi
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
A Comprehensive Review on Recent Methods and Challenges of Video Description
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.
JUNLP@Dravidian-CodeMix-FIRE2020: Sentiment Classification of Code-Mixed Tweets using Bi-Directional RNN and Language Tags
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.
Classifier Combination Approach for Question Classification for Bengali Question Answering System
Overall, the stacking approach produces the best results for fine-grained classification and achieves 87. 79% of accuracy.
Development of POS tagger for English-Bengali Code-Mixed data
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).
Preparation of Sentiment tagged Parallel Corpus and Testing its effect on Machine Translation
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.
Seq2Seq and Joint Learning Based Unix Command Line Prediction System
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.
NITS-VC System for VATEX Video Captioning Challenge 2020
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
Code-Mixed to Monolingual Translation Framework
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.
JUMT at WMT2019 News Translation Task: A Hybrid approach to Machine Translation for Lithuanian to English
In the current work, we present a description of the system submitted to WMT 2019 News Translation Shared task.
JUCBNMT at WMT2018 News Translation Task: Character Based Neural Machine Translation of Finnish to English
In the current work, we present a description of the system submitted to WMT 2018 News Translation Shared task.
SMT vs NMT: A Comparison over Hindi & Bengali Simple Sentences
All of the systems use English-Hindi and English-Bengali language pairs containing simple sentences as well as sentences of other complexity.
Identifying Bengali Multiword Expressions using Semantic Clustering
As a by-product of this experiment, we have started developing a standard lexicon in Bengali that serves as a productive Bengali linguistic thesaurus.
