Update README.md

README.md

@@ -19,20 +19,13 @@ Paper: **Detecting Loanwords in Emakhuwa: An Extremely Low-Resource {B}antu Lang
     author = "Ali, Felermino Dario Mario  and
       Lopes Cardoso, Henrique  and
       Sousa-Silva, Rui",
-    editor = "Calzolari, Nicoletta  and
-      Kan, Min-Yen  and
-      Hoste, Veronique  and
-      Lenci, Alessandro  and
-      Sakti, Sakriani  and
-      Xue, Nianwen",
     booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
     month = may,
     year = "2024",
     address = "Torino, Italia",
     publisher = "ELRA and ICCL",
     url = "https://aclanthology.org/2024.lrec-main.425",
-    pages = "4750--4759",
-    abstract = "The accurate identification of loanwords within a given text holds significant potential as a valuable tool for addressing data augmentation and mitigating data sparsity issues. Such identification can improve the performance of various natural language processing tasks, particularly in the context of low-resource languages that lack standardized spelling conventions.This research proposes a supervised method to identify loanwords in Emakhuwa, borrowed from Portuguese. Our methodology encompasses a two-fold approach. Firstly, we employ traditional machine learning algorithms incorporating handcrafted features, including language-specific and similarity-based features. We build upon prior studies to extract similarity features and propose utilizing two external resources: a Sequence-to-Sequence model and a dictionary. This innovative approach allows us to identify loanwords solely by analyzing the target word without prior knowledge about its donor counterpart. Furthermore, we fine-tune the pre-trained CANINE model for the downstream task of loanword detection, which culminates in the impressive achievement of the F1-score of 93{\%}. To the best of our knowledge, this study is the first of its kind focusing on Emakhuwa, and the preliminary results are promising as they pave the way to further advancements.",
+    pages = "4750--4759"
 }
 
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