LoResMT 2021
Workshop on Low-Resource Machine Translation
Location
- Online
Links
Schedule
| 8:00 | Opening remarks |
| 8:30 | On Meaningful Evaluation of Machine Translation Systems Mathias Müller Institut für Computerlinguistik Universität Zürich |
| 9:30 | MT for low-resource languages: progress and open problems Barry Haddow Aveni and University of Edinburgh |
| 10:30 | Challenges and Advances in MT Systems for African Languages Catherine Muthoni Gitau African Institute for Mathematical Science |
| 11:30 | Trustworthy human evaluation frameworks for MT Mona Diab Facebook and George Washington University |
| 13:00 | 🍴 |
| 14:00 | Research Papers Session 1 |
| Zero-Shot Neural Machine Translation with Self-Learning Cycle Surafel Lakew, Matteo Negri, Marco Turchi | |
| A Comparison of Different NMT Approaches to Low-Resource Dutch-Albanian Machine Translation Arbnor Rama and Eva Vanmassenhove | |
| Small-Scale Cross-Language Authorship Attribution on Social Media Comments Benjamin Murauer and Gunther Specht | |
| EnKhCorp1.0: An English-Khasi Corpus Sahinur Rahman Laskar, Abdullah Faiz Ur Rahman Khilji, Darsh Kaushik, Dr. Partha Pakray and Sivaji Bandyopadhyay | |
| 16:30 | Research Papers Session 2 |
| Active Learning for Massively Parallel Translation of Constrained Text into Low Resource Languages Zhong Zhou and Alex Waibel | |
| Manipuri-English Machine Translation using Comparable Corpus Lenin Laitonjam and Ranbir Sanasam | |
| 17:30 | ☕️ |
| 18:00 | Research Papers Session 3 |
| Morphologically-Guided Segmentation For Translation of Agglutinative Low-Resource Languages William Chen and Brett Fazio | |
| Structural Biases for Improving Transformers on Translation into Morphologically Rich Languages Paul Soulos, Sudha Rao, Caitlin Smith, Eric Rosen, Asli Celikyilmaz, R. Thomas Mccoy, Yichen Jiang, Coleman Haley, Roland Fernandez, Hamid Palangi, Jianfeng Gao and Paul Smolensky | |
| Love Thy Neighbor: Combining Two Neighboring Low-Resource Languages for Translation John Ortega, Richard Castro Mamani, and Jaime Rafael Montoya Samame | |
| Dealing with the Paradox of Quality Estimation Sugyeong Eo, Chanjun Park, Jaehyung Seo, Hyeonseok Moon, and Heuiseok Lim | |
| 20:30 | Findings of the shared Task |
| A3-108 Machine Translation System for LoResMT Shared Task @MT Summit 2021 Conference Saumitra Yadav, and Manish Shrivastava | |
| Attentive fine-tuning of Transformers for Translation of low-resourced languages @LoResMT 2021 Karthik Puranik, Adeep Hande, Ruba Priyadharshini, Thenmozi D, Anbukkarasi Sampath, Kingston Pal Thamburaj and Bharathi Raja Chakravarthi | |
| Evaluating the Performance of Back-translation for Low Resource English-Marathi Language Pair: CFILT-IITBombay @ LoResMT 2021 Aditya Jain, Shivam Mhaskar and Pushpak Bhattacharyya | |
| The UCF Systems for the LoResMT 2021 Machine Translation Shared Task William Chen and Brett Fazio | |
| Machine Translation in the Covid domain: an English-Irish case study for LoResMT 2021 Séamus Lankford, Haithem Afli and Andy Way | |
| English-Marathi Neural Machine Translation for LoResMT 2021 Vandan Mujadia and Dipti Misra Sharma | |
| 21:30 | Closing remarks |
Shared tasks
The new shared tasks focusing on the building of MT systems for COVID-related texts aims to encourage research on MT systems involving three low-resource language pairs:
- Taiwanese Sign Language <> Traditional Chinese
- English <> Irish
- English <> Marathi