LoResMT 2023
Workshop on Low-Resource Machine Translation
Location
- Dubrovnik, Croatia
Links
Important Dates
| Submission deadline | 02 March |
| Notification of acceptance | 23 March |
| Camera-ready papers deadline | 01 April |
| LoResMT workshop | 02 May |
Schedule
Day 1
| 9:00 | Opening remarks Workshop Chairs |
| 9:15 | Invited talk Crawling your way out of less-resourcedness Nikola Ljubešić Chair: Atul Kr. Ojha |
| 10:05 | Session 1: Finding Papers Chair: Sina Ahmadi |
| 10:05 | Machine Translation between Spoken Languages and Signed Languages Represented in SignWriting Zifan Jiang, Amit Moryossef, Mathias Müller, Sarah Ebling |
| 10:20 | Decipherment as Regression: Solving Historical Substitution Ciphers by Learning Symbol Recurrence Relations Nishant Kambhatla, Logan Born, Anoop Sarkar |
| 10:35 | ☕️ |
| 11:15 | Session 2: Scientific Research Papers Chair: Ekaterina Vylomova |
| 11:15 | Train Global, Tailor Local: Minimalist Multilingual Translation into Endangered Languages Zhong Zhou, Jan Niehues, Alexander Waibel |
| 11:35 | Measuring the Impact of Data Augmentation Methods for Extremely Low-Resource NMT Annie Lamar, Zeyneb N. Kaya |
| 11:55 | Language-Family Adapters for Low-Resource Multilingual Neural Machine Translation Alexandra Chronopoulou, Dario Stojanovski, Alexander Fraser |
| 12:15 | Multilingual Bidirectional Unsupervised Translation through Multilingual Finetuning and Back-Translation Bryan Li, Mohammad Sadegh Rasooli, Ajay Patel, Chris Callison-Burch |
| 12:45 | 🍴 |
| 14:15 | Applying Lessons from Low-Resource Machine Translation to Speech and Sign Language Translation Rico Sennrich Chair: Chao-Hong Liu |
| 15:00 | Session 3: Finding Papers Chair: Nathaniel Oco |
| 15:00 | Are the Best Multilingual Document Embeddings simply Based on Sentence Embeddings? Sonal Sannigrahi, Josef van Genabith, Cristina España-Bonet |
| 15:15 | Intent Identification and Entity Extraction for Healthcare Queries in Indic Languages Ankan Mullick, Ishani Mondal, Sourjyadip Ray, Raghav R, G Chaitanya, Pawan Goyal |
| 15:30 | A Simplified Training Pipeline for Low-Resource and Unsupervised Machine Translation Àlex R. Atrio, Alexis Allemann, Ljiljana Dolamic, Andrei Popescu-Belis |
| 15:45 | ☕️ |
| 16:30 | Session 4: Scientific Research Papers Chair: Valentin Malykh |
| 16:30 | Improving Neural Machine Translation of Indigenous Languages with Multilingual Transfer Learning Wei-Rui Chen, Muhammad Abdul-Mageed |
| 16:50 | PEACH: Pre-Training Sequence-to-Sequence Multilingual Models for Translation with Semi-Supervised Pseudo-Parallel Document Generation Alireza Salemi, Amirhossein Abaskohi, Sara Tavakoli, Azadeh Shakery, Yadollah Yaghoobzadeh |
| 17:10 | Investigating Lexical Replacements for Arabic-English Code-Switched Data Augmentation Injy Hamed, Nizar Habash, Slim Abdennadher, Ngoc Thang Vu |
| 17:30 | Evaluating Sentence Alignment Methods in a Low-Resource Setting: An English-YorùBá Study Case Edoardo Signoroni, Pavel Rychlý |
| 17:50 | Findings from the Bambara - French Machine Translation Competition (BFMT 2023) Ninoh Agostinho Da Silva, Tunde Ajayi, Alex Antonov, Panga Azazia Kamate, Moussa Coulibaly, Mason Del Rio, Yacouba Diarra, Sebastian Diarra, Chris Emezue, Joel Hamilcaro, Christopher Homan, Alexander Most, Joseph Mwatukange, Peter Ohue, Michael Pham, Abdoulaye Sako, Sokhar Samb, Yaya Sy, Tharindu Cyril Weerasooriya, Yacine Zahidi, Sarah Luger |
| 18:05 | Closing remarks Workshop Chairs |
Topics
- COVID-related corpora, their translations and corresponding natural language processing/machine translation systems
- Neural machine translation for low-resource languages
- Work that presents online systems for practical use by native speakers
- Word tokenisers/de-tokenisers for specific languages
- Word/morpheme segmenters for specific languages
- Alignment/Re-ordering tools for specific language pairs
- Use of morphology analysers and/or morpheme segmenters in MT
- Multilingual/cross-lingual natural language processing tools for machine translation
- Corpora creation and curation technologies for low-resource languages
- Review of available parallel corpora for low-resource languages
- Research and review papers of machine translation methods for low-resource languages
- Machine translation systems/methods (for example, rule-based, statistical machine translation, neural machine translation) for low-resource languages
- Pivot machine translation for low-resource languages
- Zero-shot machine translation for low-resource languages
- Fast building of machine translation systems for low-resource languages
- Re-usability of existing machine translation systems for low-resource languages
- Machine translation for language preservation