I am an MSc student in Computer Engineering at Boğaziçi University in Istanbul, Turkey, advised by Susan Michele Üsküdarlı. I am also a teaching assistant in the same department and a member of TABILAB. My research interests include computational linguistics, linguistic variation and phonology. I’m hoping to merge my interests in linguistics and computer science in my research.
The recent advances in natural language processing have predominantly favored well-resourced English-centric models, resulting in a significant gap with low-resource languages. In this work, we introduce the language model TURNA, which is developed for the low-resource language Turkish and is capable of both natural language understanding and generation tasks. TURNA is pretrained with an encoder-decoder architecture based on the unified framework UL2 with a diverse corpus that we specifically curated for this purpose. We evaluated TURNA with three generation tasks and five understanding tasks for Turkish. The results show that TURNA outperforms several multilingual models in both understanding and generation tasks, and competes with monolingual Turkish models in understanding tasks. TURNA is made available at https://huggingface.co/boun-tabi-LMG/TURNA .
@misc{uludoğan2024turna,title={TURNA: A Turkish Encoder-Decoder Language Model for Enhanced Understanding and Generation},author={Uludoğan, Gökçe and Balal, Zeynep Yirmibeşoğlu and Akkurt, Furkan and Türker, Melikşah and Güngör, Onur and Üsküdarlı, Susan},year={2024},eprint={2401.14373},archiveprefix={arXiv},primaryclass={cs.CL},}
BoAT v2 - A Web-Based Dependency Annotation Tool with Focus on Agglutinative Languages
Salih
Furkan Akkurt, Büşra
Marşan, and Susan
Uskudarli
In Proceedings of The International Conference and Workshop on Agglutinative Language Technologies as a challenge of Natural Language Processing (ALTNLP), Jun 2022
The value of quality treebanks is steadily increasing due to the crucial role they play in the development of natural language processing tools. The creation of such treebanks is enormously labor-intensive and time-consuming. Especially when the size of treebanks is considered, tools that support the annotation process are essential. Various annotation tools have been proposed, however, they are often not suitable for agglutinative languages such as Turkish. BOAT-v1 was developed for annotating dependency relations and was subsequently used to create the manually annotated BOUN Treebank (UD_Turkish-BOUN). In this work, we report on the design and implementation of a dependency annotation tool (BOAT-v2) based on the experiences gained from the use of BOAT-v1, which revealed several opportunities for improvement. BOAT-v2 is a multi-user and web-based dependency annotation tool that is designed with a focus on the annotator user experience to yield valid annotations. The main obiectives of the tool are to: (1) support creating valid and consistent annotations with increased speed, (2) significantly improve the user experience of the annotator, (3) support collaboration among annotators, and (4) provide an open-source and easily deployable web-based annotation tool with a flexible application programming interface (API) to benefit the scientific community. This paper discusses the requirements elicitation, design, and implementation of BOAT-v2 along with examples.
@inproceedings{boat-altnlp,author={Furkan Akkurt, Salih and Marşan, Büşra and Uskudarli, Susan},title={{BoAT v2 - A Web-Based Dependency Annotation Tool with Focus on Agglutinative Languages}},booktitle={Proceedings of The International Conference and Workshop on Agglutinative Language Technologies as a challenge of Natural Language Processing (ALTNLP)},year={2022},month=jun,}
