Italian-Chinese Neural Machine Translation: results and lessons learnt

Giovanni Delnevo, Marcus Im, Rita Tse, Chan Tong Lam, Su Kit Tang, Paola Salomoni, Giovanni Pau, Vittorio Ghini, Silvia Mirri

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Today, access to the Internet provides access to various forms of knowledge like free online lecture series offered by prestigious universities, massive open online courses, films and books, and Wikipedia. In addition, it is possible to join online communities on any topic of interest, get to know people with common interests, exchange thoughts and participate in debates. To enable access to these unprecedented knowledge bases, it is crucial to be able to translate texts into any language known by users. For this reason, Machine Translation has been a very active research field for the last thirty years. In this paper, we investigate the task of Chinese-Italian translations by exploiting Neural Machine Translation approaches. We trained several deep neural networks starting from two already available datasets containing Chinese-Italian parallel corpora. Then, we compared their performance against some of the most common machine translation services freely available online. In particular, we take advantage of Microsoft Translator, Google Translate, DeepL, and ModernMT.

Original languageEnglish
Title of host publicationGoodIT 2023 - Proceedings of the 2023 ACM Conference on Information Technology for Social Good
PublisherAssociation for Computing Machinery
Number of pages7
ISBN (Electronic)9798400701160
Publication statusPublished - 6 Sept 2023
Event3rd ACM Conference on Information Technology for Social Good, GoodIT 2023 - Lisbon, Portugal
Duration: 6 Sept 20238 Sept 2023

Publication series

NameACM International Conference Proceeding Series


Conference3rd ACM Conference on Information Technology for Social Good, GoodIT 2023


  • Big Data
  • Italian Chinese Translation
  • Neural Machine Translation
  • Transformer


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