Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,67 @@
+---
+license: mit
+tags:
+- machine-translation
+language:
+- min
+- ind
+---
+
+# minangnlp_mt
+
+In this work, we create Minangkabau–Indonesian (MIN-ID) parallel corpus by using Wikipedia. We obtain 224,180 Minangkabau and
+
+510,258 Indonesian articles, and align documents through title matching, resulting in 111,430 MINID document pairs.
+
+After that, we do sentence segmentation based on simple punctuation heuristics and obtain 4,323,315 Minangkabau sentences. We
+
+then use the bilingual dictionary to translate Minangkabau article (MIN) into Indonesian language (ID'). Sentence alignment is conducted using
+
+ROUGE-1 (F1) score (unigram overlap) (Lin, 2004) between ID’ and ID, and we pair each MIN sentencewith an ID sentence based on the highest ROUGE1.
+
+We then discard sentence pairs with a score of less than 0.5 to result in 345,146 MIN-ID parallel sentences.
+
+We observe that the sentence pattern in the collection is highly repetitive (e.g. 100k sentences are about biological term definition). Therefore,
+
+we conduct final filtering based on top-1000 trigram by iteratively discarding sentences until the frequency of each trigram equals to 100. Finally, we
+
+obtain 16,371 MIN-ID parallel sentences and conducted manual evaluation by asking two native Minangkabau speakers to assess the adequacy and
+
+fluency (Koehn and Monz, 2006). The human judgement is based on scale 1–5 (1 means poor quality and 5 otherwise) and conducted against 100 random
+
+samples. We average the weights of two annotators before computing the overall score, and we achieve 4.98 and 4.87 for adequacy and fluency respectively.
+
+This indicates that the resulting corpus is high-quality for machine translation training.
+
+## Dataset Usage
+
+Run `pip install nusacrowd` before loading the dataset through HuggingFace's `load_dataset`.
+
+## Citation
+
+```
+@inproceedings{koto-koto-2020-towards,
+    title = "Towards Computational Linguistics in {M}inangkabau Language: Studies on Sentiment Analysis and Machine Translation",
+    author = "Koto, Fajri  and
+      Koto, Ikhwan",
+    booktitle = "Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation",
+    month = oct,
+    year = "2020",
+    address = "Hanoi, Vietnam",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2020.paclic-1.17",
+    pages = "138--148",
+}
+```
+
+## License
+
+MIT
+
+## Homepage
+
+[https://github.com/fajri91/minangNLP](https://github.com/fajri91/minangNLP)
+
+### NusaCatalogue
+
+For easy indexing and metadata: [https://indonlp.github.io/nusa-catalogue](https://indonlp.github.io/nusa-catalogue)