no code implementations • WMT (EMNLP) 2020 • Amit Kumar, Rupjyoti Baruah, Rajesh Kumar Mundotiya, Anil Kumar Singh
This paper reports the results for the Machine Translation (MT) system submitted by the NLPRL team for the Hindi – Marathi Similar Translation Task at WMT 2020.
no code implementations • loresmt (AACL) 2020 • Amit Kumar, Rajesh Kumar Mundotiya, Anil Kumar Singh
This paper reports a Machine Translation (MT) system submitted by the NLPRL team for the Bhojpuri–Hindi and Magahi–Hindi language pairs at LoResMT 2020 shared task.
no code implementations • EMNLP (WNUT) 2020 • Rajesh Kumar Mundotiya, Rupjyoti Baruah, Bhavana Srivastava, Anil Kumar Singh
The Coronavirus pandemic has been a dominating news on social media for the last many months.
no code implementations • RANLP 2021 • Pranav Nair, Anil Kumar Singh
Repetition in natural language generation reduces the informativeness of text and makes it less appealing.
no code implementations • WMT (EMNLP) 2020 • Rupjyoti Baruah, Rajesh Kumar Mundotiya, Amit Kumar, Anil Kumar Singh
This paper describes the results of the system that we used for the WMT20 very low resource (VLR) supervised MT shared task.
no code implementations • ICON 2020 • Samapika Roy, Sukhada Sukhada, Anil Kumar Singh
While the creativity seen in NHs is fascinating for language researchers, it poses a computational challenge for Natural Language Processing researchers.
no code implementations • RANLP 2021 • Pranav Nair, Anil Kumar Singh
Large scale pretrained models have demonstrated strong performances on several natural language generation and understanding benchmarks.
no code implementations • 21 May 2023 • Amit Kumar, Shantipriya Parida, Ajay Pratap, Anil Kumar Singh
One reason for this is the relative morphological richness of Indian languages, while another is that most of them fall into the extremely low resource or zero-shot categories.
no code implementations • 31 Mar 2023 • Amit Kumar, Ajay Pratap, Anil Kumar Singh
Generative Adversarial Networks (GAN) offer a promising approach for Neural Machine Translation (NMT).
no code implementations • 3 Mar 2023 • Amit Kumar, Rupjyoti Baruah, Ajay Pratap, Mayank Swarnkar, Anil Kumar Singh
If the evaluation is as rigorous as resource-rich languages, both Neural Machine Translation (NMT) and Statistical Machine Translation (SMT) can produce good results with such large amounts of data.
no code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Ankur Sonawane, Sujeet Kumar Vishwakarma, Bhavana Srivastava, Anil Kumar Singh
We address this problem by generating a large corpus of artificial inflectional errors for training GEC models.
no code implementations • 14 Sep 2020 • Rajesh Kumar Mundotiya, Shantanu Kumar, Ajeet kumar, Umesh Chandra Chaudhary, Supriya Chauhan, Swasti Mishra, Praveen Gatla, Anil Kumar Singh
The lower baseline F1-scores from the NER tool obtained by using Conditional Random Fields models are 96. 73 for Bhojpuri, 93. 33 for Maithili and 95. 04 for Magahi.
no code implementations • 29 Apr 2020 • Rajesh Kumar Mundotiya, Manish Kumar Singh, Rahul Kapur, Swasti Mishra, Anil Kumar Singh
Corpus preparation for low-resource languages and for development of human language technology to analyze or computationally process them is a laborious task, primarily due to the unavailability of expert linguists who are native speakers of these languages and also due to the time and resources required.
no code implementations • WS 2019 • Amit Kumar, Anil Kumar Singh
This paper describes the Machine Translation system for Tamil-English Indic Task organized at WAT 2019.
1 code implementation • WS 2018 • Shreyansh Singh, Avi Chawla, Ayush Sharma, Anil Kumar Singh
This paper describes our submission system for the Shallow Track of Surface Realization Shared Task 2018 (SRST'18).
1 code implementation • 21 Nov 2018 • Saurav Jha, Akhilesh Sudhakar, Anil Kumar Singh
The ambiguities introduced by the recombination of morphemes constructing several possible inflections for a word makes the prediction of syntactic traits in Morphologically Rich Languages (MRLs) a notoriously complicated task.
1 code implementation • 21 Nov 2018 • Saurav Jha, Akhilesh Sudhakar, Anil Kumar Singh
Out-of-vocabulary (OOV) words can pose serious challenges for machine translation (MT) tasks, and in particular, for low-resource language (LRL) pairs, i. e., language pairs for which few or no parallel corpora exist.
no code implementations • WS 2018 • Soumil Mandal, Anil Kumar Singh
An accurate language identification tool is an absolute necessity for building complex NLP systems to be used on code-mixed data.
no code implementations • COLING 2018 • Divyanshu Gupta, Gourav Dhakad, Jayprakash Gupta, Anil Kumar Singh
Text language Identification is a Natural Language Processing task of identifying and recognizing a given language out of many different languages from a piece of text.
1 code implementation • COLING 2018 • Devang Kulshreshtha, Pranav Goel, Anil Kumar Singh
Social media based micro-blogging sites like Twitter have become a common source of real-time information (impacting organizations and their strategies, and are used for expressing emotions and opinions.
no code implementations • WS 2018 • Shashwat Trivedi, Harsh Rangwani, Anil Kumar Singh
This paper describes the best performing system for the shared task on Named Entity Recognition (NER) on code-switched data for the language pair Spanish-English (ENG-SPA).
no code implementations • WS 2018 • Krishnkant Swarnkar, Anil Kumar Singh
The contrast between the contextual and general meaning of a word serves as an important clue for detecting its metaphoricity.
no code implementations • SEMEVAL 2018 • Harsh Rangwani, Devang Kulshreshtha, Anil Kumar Singh
This paper describes our participation in SemEval 2018 Task 3 on Irony Detection in Tweets.
no code implementations • 20 Dec 2017 • Anil Kumar Singh, Akhilesh Sudhakar
Ideas from forensic linguistics are now being used frequently in Natural Language Processing (NLP), using machine learning techniques.
no code implementations • IJCNLP 2017 • Anil Kumar Singh, Avijit Thawani, Mayank Panchal, Anubhav Gupta, Julian McAuley
Unlike Entity Disambiguation in web search results, Opinion Disambiguation is a relatively unexplored topic.
no code implementations • WS 2017 • Pranav Goel, Anil Kumar Singh
This paper describes an ensemble system submitted as part of the LSDSem Shared Task 2017 - the Story Cloze Test.
no code implementations • LREC 2012 • Anil Kumar Singh
The usefulness of annotated corpora is greatly increased if there is an associated tool that can allow various kinds of operations to be performed in a simple way.
no code implementations • LREC 2012 • Rahul Agarwal, Bharat Ram Ambati, Anil Kumar Singh
It is essential to ensure the quality of a treebank before it can be deployed for other purposes.