Title
Assessing the impact of real-time machine translation on multilingual meetings in global software projects
Abstract
Communication in global software development is hindered by language differences in countries with a lack of English speaking professionals. Machine translation is a technology that uses software to translate from one natural language to another. The progress of machine translation systems has been steady in the last decade. As for now, machine translation technology is particularly appealing because it might be used, in the form of cross-language chat services, in countries that are entering into global software projects. However, despite the recent progress of the technology, we still lack a thorough understanding of how real-time machine translation affects communication. In this paper, we present a set of empirical studies with the goal of assessing to what extent real-time machine translation can be used in distributed, multilingual requirements meetings instead of English. Results suggest that, despite far from 100 % accurate, real-time machine translation is not disruptive of the conversation flow and, therefore, is accepted with favor by participants. However, stronger effects can be expected to emerge when language barriers are more critical. Our findings add to the evidence about the recent advances of machine translation technology and provide some guidance to global software engineering practitioners in regarding the losses and gains of using English as a lingua franca in multilingual group communication, as in the case of computer-mediated requirements meetings.
Year
DOI
Venue
2016
10.1007/s10664-015-9372-x
Empirical Software Engineering
Keywords
Field
DocType
Global software development,Machine translation,Distributed meetings,Computer-mediated communication,Controlled experiment
Data science,Conversation,English as a lingua franca,Systems engineering,Software engineering,Computer science,Machine translation,Natural language,Computer-mediated communication,Experimental software engineering,Language industry,Empirical research
Journal
Volume
Issue
ISSN
21
3
1382-3256
Citations 
PageRank 
References 
0
0.34
20
Authors
4
Name
Order
Citations
PageRank
Fabio Calefato141437.84
Filippo Lanubile21628124.29
Tayana Conte346981.13
Rafael Prikladnicki484086.35