Kamal Deep

Fixing paper assignments

  1. Please select all papers that belong to the same person.
  2. Indicate below which author they should be assigned to.
Provide a valid ORCID iD here. This will be used to match future papers to this author.
Provide the name of the school or the university where the author has received or will receive their highest degree (e.g., Ph.D. institution for researchers, or current affiliation for students). This will be used to form the new author page ID, if needed.

TODO: "submit" and "cancel" buttons here

2020

pdf bib
Punjabi to English Bidirectional NMT System
Kamal Deep | Ajit Kumar | Vishal Goyal
Proceedings of the 17th International Conference on Natural Language Processing (ICON): System Demonstrations

Machine Translation is ongoing research for last few decades. Today, Corpus-based Machine Translation systems are very popular. Statistical Machine Translation and Neural Machine Translation are based on the parallel corpus. In this research, the Punjabi to English Bidirectional Neural Machine Translation system is developed. To improve the accuracy of the Neural Machine Translation system, Word Embedding and Byte Pair Encoding is used. The claimed BLEU score is 38.30 for Punjabi to English Neural Machine Translation system and 36.96 for English to Punjabi Neural Machine Translation system.
Search
Co-authors
Venues
Fix data