2026-04-14T03:27:45Zhttps://recercat.cat/oai/request

oai:recercat.cat:10230/541402025-12-23T20:52:49Zcom_2072_6col_2072_452954

urn:hdl:10230/54140 Building a Catalan-Chinese parallel corpus from Wikipedia for use in machine translation Zhou, Chenyue Parallel corpus Data mining Corpus quality Machine translation Catalan Chinese Low-resource languages Treball de fi de màster en Lingüística Teòrica i Aplicada. Directora: Dra. Maite Melero The lack of parallel corpora is one of the biggest challenges hindering progress in Machine Translation for low-resource languages. In this work, we crawl and filter parallel sentences in Catalan and Chinese from Wikipedia in order to compile a parallel corpus of good quality. This paper describes the processes we follow to build the corpus, including mining the text data, computing sentence embeddings, extracting sentence alignment and filtering for better corpus quality. We manually audit the corpus quality based on an error taxonomy. Results show that the automatic filtering we applied makes a great improvement in the quality of our web-crawled corpus. The corpus is later used as training data to finetune a multilingual Machine Translation (MT) system in both CA→ZH and ZH→CA directions. Results show that finetuning with our corpus successfully managed to improve BLEU score in both directions on the Flores-101 public benchmark test sets, which demonstrates the importance of corpus in MT and the quality of our Catalan-Chinese parallel corpus. 2022-09-21T16:55:53Z 2022-09-21T16:55:53Z 2022-09-21 info:eu-repo/semantics/masterThesis Llicència CC Reconeixement-NoComercial-SenseObraDerivada 4.0 Internacional (CC BY-NC-ND 4.0) https://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess