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Found 26 papers, 1 papers with code
CNLP-NITS @ LongSumm 2021: TextRank Variant for Generating Long Summaries
The huge influx of published papers in the field of machine learning makes the task of summarization of scholarly documents vital, not just to eliminate the redundancy but also to provide a complete and satisfying crux of the content.
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.
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.
Language Resource Building and English-to-Mizo Neural Machine Translation Encountering Tonal Words
Multilingual country like India has an enormous linguistic diversity and has an increasing demand towards developing language resources such that it will outreach in various natural language processing applications like machine translation.
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.
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.
EnKhCorp1.0: An English–Khasi Corpus
In machine translation, corpus preparation is one of the crucial tasks, particularly for lowresource pairs.
Hindi-Marathi Cross Lingual Model
We have participated in WMT20 shared task of similar language translation on Hindi-Marathi pair.
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.
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.
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.
Breaking the Silence Detecting and Mitigating Gendered Abuse in Hindi, Tamil, and Indian English Online Spaces
Online gender-based harassment is a widespread issue limiting the free expression and participation of women and marginalized genders in digital spaces.
TRAVID: An End-to-End Video Translation Framework
In today's globalized world, effective communication with people from diverse linguistic backgrounds has become increasingly crucial.
Deep Neural Network for Musical Instrument Recognition using MFCCs
Musical instrument recognition is the task of instrument identification by virtue of its audio.
English to Hindi Multi-modal Neural Machine Translation and Hindi Image Captioning
With the widespread use of Machine Trans-lation (MT) techniques, attempt to minimizecommunication gap among people from di-verse linguistic backgrounds.
Neural Machine Translation: Hindi-Nepali
Also, we have achieved BLEU score 53. 7 (Hindi to Nepali) and 49. 1 (Nepali to Hindi) in contrastive system type.
JU NITM at IJCNLP-2017 Task 5: A Classification Approach for Answer Selection in Multi-choice Question Answering System
The main aim of this shared task is to choose the correct option for each multi-choice question.
NITMZ-JU at IJCNLP-2017 Task 4: Customer Feedback Analysis
In this paper, we describe a deep learning framework for analyzing the customer feedback as part of our participation in the shared task on Customer Feedback Analysis at the 8th International Joint Conference on Natural Language Processing (IJCNLP 2017).
