Johann Roturier: Localizing apps: a practical guide for translators and translation students

Flournoy, Raymond

doi:10.1007/s10590-015-9173-4

Cited by 2 publications

(2 citation statements)

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“…To decrease the translation time, localization companies take the help of machine translation (MT). Human annotators use the MT system for generating initial translations and postedit the system's output to increase efficiency in computer-assisted translation tools (Flournoy and Duran, 2009;Skadin , š et al, 2014). When producing high-quality translations, costs can be saved by decreasing the annotator's time on editing and making the localization process cheaper.…”

Section: Introductionmentioning

confidence: 99%

Analyzing Challenges in Neural Machine Translation for Software Localization

Koneru,

Huck,

Exel

et al. 2023

Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics

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Advancements in Neural Machine Translation (NMT) greatly benefit the software localization industry by decreasing the post-editing time of human annotators. Although the volume of the software being localized is growing significantly, techniques for improving NMT for user interface (UI) texts are lacking. These UI texts have different properties than other collections of texts, presenting unique challenges for NMT. For example, they are often very short, causing them to be ambiguous and needing additional context (button, title text, a table item, etc.) for disambiguation. However, no such UI data sets are readily available with contextual information for NMT models to exploit. This work aims to provide a first step in improving UI translations and highlight its challenges. To achieve this, we provide a novel multilingual UI corpus collection (∼ 1.3M for English ↔ German) with a targeted test set and analyze the limitations of state-of-the-art methods on this challenging task. Specifically, we present a targeted test set for disambiguation from English to German to evaluate reliably and emphasize UI translation challenges. Furthermore, we evaluate several state-of-the-art NMT techniques from domain adaptation and document-level NMT on this challenging task. All the scripts to replicate the experiments and data sets are available here. 1,2 Context Source Context Target Source Word Target Word %s was written onto %s Select Image %s wurde auf %s geschrieben Abbild auswählen Image Abbild, Bilder

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Section: Introductionmentioning

confidence: 99%

Analyzing Challenges in Neural Machine Translation for Software Localization

Koneru,

Huck,

Exel

et al. 2023

Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics

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“…Local software development companies can be empowered to work for the administration, public and private sectors. In this scenario, many organizations are taking lead to implement and support localization (Roturier, 2015(Roturier, , 2005.…”

Section: Introductionmentioning

confidence: 99%

A successful recipe for localization: a case of GIMP (GNU image manipulation program)

Shirude

Joshi

2022

JIBR

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Purpose Free Open Source Softwares (FOSS) witnessed the development of many very good alternatives to proprietary softwares. These free softwares can be localized in several local languages. This paper aims to illustrate a very interesting empirical investigation on FOSS. Several significant benefits of localization are described in introduction and subsequent sections. Design/methodology/approach Although the localization process is standard and well documented for most of the FOSS, it is a more complex task as it involves coordination among developers, linguists and domain experts. Hence, a very few open source softwares are successfully localized in Indian languages. In this paper, the authors present an approach that they have used for GIMP (GNU Image Manipulation Program) software Marathikaran (localization in Marathi language) project of by Rajya Marathi Vikas Sanstha of Maharashtra Government (RMVS), India. Findings This localization project has been described by RMVS as a pilot project that would guide such similar localizations in many other Indian languages for other popular open source softwares. Social implications The localization work overcomes the general misconception that regional languages are good only for communication (Boli Bhasha) but cannot be used for dissemination of knowledge (Gyan Bhasha). This work is notably contributing to language preservation, language revitalization and Digital India Initiative. Originality/value This work is the pioneering work in this domain for Marathi language with respect to GIMP. The authors presented systematic steps used to localize the GIMP software in Marathi language (from 2% to 100%).

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Johann Roturier: Localizing apps: a practical guide for translators and translation students

Cited by 2 publications

References 0 publications

Analyzing Challenges in Neural Machine Translation for Software Localization

Analyzing Challenges in Neural Machine Translation for Software Localization

A successful recipe for localization: a case of GIMP (GNU image manipulation program)

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