Evaluating the State-of-the-Art Sentence Alignment System on Literary Texts

SIGNORONI, Edoardo. Evaluating the State-of-the-Art Sentence Alignment System on Literary Texts. In Horák, Rychlý, Rambousek. Recent Advances in Slavonic Natural Language Processing (RASLAN 2021). Brno: Tribun EU, 2021, p. 115-124. ISBN 978-80-263-1670-1.

Basic information

• Original name: Evaluating the State-of-the-Art Sentence Alignment System on Literary Texts
• Authors: SIGNORONI, Edoardo (380 Italy, guarantor, belonging to the institution).
• Edition: Brno, Recent Advances in Slavonic Natural Language Processing (RASLAN 2021), p. 115-124, 10 pp. 2021.
• Publisher: Tribun EU

Other information

• Original language: English
• Type of outcome: Proceedings paper
• Field of Study: 10200 1.2 Computer and information sciences
• Country of publisher: Czech Republic
• Confidentiality degree: is not subject to a state or trade secret
• Publication form: printed version "print"
• WWW: Domovská stránka workshopu Full text PDF
• RIV identification code: RIV/00216224:14330/21:00125090
• Organization unit: Faculty of Informatics
• ISBN: 978-80-263-1670-1
• ISSN: 2336-4289
• Keywords in English: Parallel corpora; Automatic alignment; Literary text

Abstract

Sentence alignment is a useful task with many applications in Natural Language Processing and Digital Humanities. This paper presents an evaluation of Vecalign, the state-of-the-art method for automatic sen- tence alignment, on two bilingual corpora built from literary texts. This preliminary study shows that Vecalign performs well for literary texts and gives insights on its remaining issues through a qualitative evaluation of the output alignments.

Links

• EF19_073/0016943, research and development project: Name: Interní grantová agentura Masarykovy univerzity
• MUNI/IGA/1334/2021, interní kód MU: Name: A New Machine Translation-based approach to Parallel Corpora Alignment

Investor: Masaryk University