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 • AACL (WAT) 2020 • Rupjyoti Baruah, Rajesh Kumar Mundotiya
In this manuscript, we (team name is NLPRL) describe systems description that was submitted to the translation shared tasks at WAT 2020.
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 • 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 • 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 • 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.