NMT and PBSMT Error Analyses in English to Brazilian Portuguese Automatic Translations

Author(s):Show less -

Caseli, Helena de Medeiros ; Inacio, Marcio Lima ; Calzolari, N ; Bechet, F ; Blache, P ; Choukri, K ; Cieri, C ; Declerck, T ; Goggi, S ; Isahara, H ; Maegaard, B ; Mariani, J ; Mazo, H ; Moreno, A ; Odijk, J ; Piperidis, S

• Document type: Journal article
• Source: PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION (LREC 2020); v. N/A, p. 7-pg., 2020-01-01.

Abstract

Machine Translation (MT) is one of the most important natural language processing applications. Independently of the applied MT approach, a MT system automatically generates an equivalent version (in some target language) of an input sentence (in some source language). Recently, a new MT approach has been proposed: neural machine translation (NMT). NMT systems have already outperformed traditional phrase-based statistical machine translation (PBSMT) systems for some pairs of languages. However, any MT approach outputs errors. In this work we present a comparative study of MT errors generated by a NMT system and a PBSMT system trained on the same English - Brazilian Portuguese parallel corpus. This is the first study of this kind involving NMT for Brazilian Portuguese. Furthermore, the analyses and conclusions presented here point out the specific problems of NMT outputs in relation to PBSMT ones and also give lots of insights into how to implement automatic post-editing for a NMT system. Finally, the corpora annotated with MT errors generated by both PBSMT and NMT systems are also available. (AU)

• FAPESP's process: 16/21317-0 - Semantic driven automated post-editing for Brazilian Portuguese
• Grantee: Marcio Lima Inácio
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• FAPESP's process: 16/13002-0 - MMeaning - multimodal distributional semantic models
• Grantee: Helena de Medeiros Caseli
• Support Opportunities: Regular Research Grants