NMTVis - Extended Neural Machine Translation Visualization System

DOI

NMTVis is a web-based visual analytics system to analyze, understand, and correct translations generated with neural machine translation. First, a document can be translated using a neural machine translation model (we support an LSTM-based and the Transformer architecture). Afterward, users can find mistranslated sentences, explore and correct these sentences and retrain the model to generate a better translation for the whole document. Our approach targets the correction of domain-specific documents. This extended version of our visual analytics system provides additional visualization and interaction techniques as well as scripts for computer-based evaluation of our approach. You can find important information about our system here and an introduction to our system here.

You may find the most recent version of the source code on GitHub: https://github.com/MunzT/NMTVis

Trained models for translation from German to English and vice versa can be found here: https://doi.org/10.18419/darus-1850

Identifier
DOI https://doi.org/10.18419/darus-2124
Related Identifier IsCitedBy https://doi.org/10.1016/j.cag.2021.12.003
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/darus-2124
Provenance
Creator Munz, Tanja ORCID logo; Väth, Dirk; Kuznecov, Paul; Vu, Ngoc Thang; Weiskopf, Daniel ORCID logo
Publisher DaRUS
Contributor Munz, Tanja
Publication Year 2022
Funding Reference DFG EXC 2075 - 390740016
Rights MIT License; info:eu-repo/semantics/openAccess; https://spdx.org/licenses/MIT.html
OpenAccess true
Contact Munz, Tanja (University of Stuttgart)
Representation
Resource Type Dataset
Format application/zip
Size 34345661
Version 1.0
Discipline Other