NMTVis - Neural Machine Translation Visualization System (doi:10.18419/darus-1849)

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Part 1: Document Description
Part 2: Study Description
Part 5: Other Study-Related Materials
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Document Description

Citation

Title:

NMTVis - Neural Machine Translation Visualization System

Identification Number:

doi:10.18419/darus-1849

Distributor:

DaRUS

Date of Distribution:

2021-05-26

Version:

1

Bibliographic Citation:

Munz, Tanja; Väth, Dirk; Kuznecov, Paul; Vu, Ngoc Thang; Weiskopf, Daniel, 2021, "NMTVis - Neural Machine Translation Visualization System", https://doi.org/10.18419/darus-1849, DaRUS, V1

Study Description

Citation

Title:

NMTVis - Neural Machine Translation Visualization System

Identification Number:

doi:10.18419/darus-1849

Authoring Entity:

Munz, Tanja (University of Stuttgart)

Väth, Dirk (University of Stuttgart)

Kuznecov, Paul (University of Stuttgart)

Vu, Ngoc Thang (University of Stuttgart)

Weiskopf, Daniel (University of Stuttgart)

Grant Number:

EXC 2075 - 390740016

Distributor:

DaRUS

Access Authority:

Munz, Tanja

Depositor:

Munz, Tanja

Date of Deposit:

2021-05-11

Study Scope

Keywords:

Computer and Information Science, Visual Analytics, Neural Machine Translation, Machine Learning, Transformer, Long short-term memory, Beam Search, Attention

Abstract:

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.

Notes:

You may find the most recent version of the source code on GitHub: <a href="https://github.com/MunzT/NMTVis">https://github.com/MunzT/NMTVis</a> <br> Trained models for translation from German to English and vice versa can be found here: <a href="https://doi.org/10.18419/darus-1850">https://doi.org/10.18419/darus-1850</a>

Methodology and Processing

Sources Statement

Data Access

Notes:

The MIT License (MIT) <br> <br> Copyright (c) 2021 Tanja Munz, Dirk Väth, Paul Kuznecov, Ngoc Thang Vu, Daniel Weiskopf <br> <br> Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: <br> <br> The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. <br> <br> THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Other Study Description Materials

Related Publications

Citation

Bibliographic Citation:

T. Munz, D. Väth, P. Kuznecov, N. T. Vu, and D. Weiskopf. "Visual-Interactive Neural Machine Translation". Graphics Interface. 2021.

Other Study-Related Materials

Label:

nmtvis.zip

Text:

Source code of our visual analytics system

Notes:

application/zip