A Small Study on Real-Time Language Translation and Its Contribution to Language Learning

Total Page:16

File Type:pdf, Size:1020Kb

A Small Study on Real-Time Language Translation and Its Contribution to Language Learning A small study on real-time language translation and its contribution to language learning. SUBMITTED IN PARTIAL FULLFILLMENT FOR THE DEGREE OF MASTER OF SCIENCE EVIE JANSSEN 10829318 MASTER INFORMATION STUDIES HUMAN-CENTERED MULTIMEDIA FACULTY OF SCIENCE UNIVERSITY OF AMSTERDAM July 3, 2015 1st Supervisor 2nd Supervisor Dr. Daniel Buzzo Dr. Jacobijn Sandberg UvA UvA A small study on real-time language translation and its contribution to language learning. Evie Janssen University of Amsterdam, Graduate School of Informatics Science Park 904, Amsterdam [email protected] ABSTRACT translators is exciting. However, we must not forget This paper explores the new real-time machine how important it is to actually learn a foreign translation technology and its effect on second language. Within a conversation, words take on language learning motivation. Based on a field different meanings based on the understanding of the experiment among 18 non-native Dutch persons, I language. Communication is based on consciousness conclude that the use of speech translation enhances as meaning is negotiated for achieving possible the motivation and self-confidence when understanding (Bakhtin, 1981; Klein, 1986). communicating in a second language. In addition, the Therefore, learning and understanding a foreign use of image translation has a positive influence on language is important to communicate properly and vocabulary learning. Overall, real-time machine connect with a new culture. In addition, learning a translation stimulates second language learners to second language has far more advantages such as maintain the executive motivation. creating job opportunities and even keeping your brain healthy (Mechelli et al., 2004). Keywords L2 learning, learning motivation, machine translation The quote from Nelson Mandela, stated at the beginning of this section, is poetry. However, I think we all know in our hearts that his statement is true. 1. INTRODUCTION Talking to someone in their own language is showing “If you talk to a man in a language he understands, them respect, and with respect comes understanding. I that goes to his head. If you talk to him in his find this an admonitory quote for the excessive use of language that goes to his heart” (Nelson Mandela). innovative technologies such as RMT. No technology can ever truly substitute the benefits of knowing Today, the digital age of internet and mobile second languages. However, I do believe that technologies are providing global mobility of technology can stimulate the motivation within the knowledge. Virtual learning environments have process of learning a second language. In this paper I diversified the way of learning by broadening the will explore this area of tension. possibilities of gaining knowledge. As are learning environments in language learning. Moreover, the There are many advantages for knowing other motivation of language learning is supported in new languages and there are many factors taking place in ways through mobile learning and translation the process of successful language acquisition applications. (Skehan, 1989; Saville-Troike, 2006). Among all these factors, motivation plays an important role in Learning has been re-assessed as a personalized and L2 learning (Gardner, 1985; Masgoret & Gardner, learner-centred activity (Leadbetter, 2005). According 2003; Dörnyei, 2005). to Sharples et al. (2005), “so too are new digital technologies offering personalised services.” At the From the experience and work of the linguist Steve beginning of 2015 Google and Skype both launched Kaufmann, contextual and personal learning what they believe to be the next level of machine environments are the stimulating factors for language language translation: real-time machine translation learning motivation. A learner has to discover the (RMT). By using phones' cameras or speech, words and the phrases that he or she is going to need languages can be translated immediately and allow (Kaufmann, 2013). The importance of contextual seamless chat between people. Barak Turovsky, learning environments, therefore, presents the interest product Lead of Google Translate, states in a blog for exploring the effect of RMT on language learning post the following: "today's updates take us one step motivation. closer to a world where language is no longer a barrier to discovering information or connecting with 1 1 Source: http://googleblog.blogspot.nl/2015/01/hallo-hola- each other. ” Altogether, the potential of real-time ola-more-powerful-translate.html The goal of this paper is to evaluate the effectiveness Therefore, it is important to get emotionally engaged of RMT on the motivation of non-native Dutch users with the language and the context that we‟re learning to learn Dutch as a second language. What if we can from. In other words, learning from material that we use RMT in such a way that translated content can like and find interesting has resonance. become the bridge between discovering information and stimulating language learning? Section 2 presents New conceptions of learning are evolving because of the evidence from the literature and an interview the convergence of mobile and personal technologies. conducted with an expert in the field of linguistics. In Table 1 shows the similarities between new learning section 3 the main research question will be and new technology (Sharples, Taylor, Vavoula, introduced and the methods for answering this 2005). question will be described. This includes an experiment with the new RMT functions among non- New Learning New Technology native Dutch persons who (want to) learn Dutch. Personalized Personal Section 4 and 5 will present the results of my study Learner centred User centred and discuss the findings. I conclude by offering Situated Mobile suggestions for future work. Collaborative Networked Ubiquitous Ubiquitous 2. RELATED WORK Lifelong Durable Table 1 - Convergence between learning and technology 2.1 Second Language Learning A second language (L2) refers to a language an The study of McGroarty (2001) explains the role and individual learns that is not his/her mother tongue, but contribution of different social contexts in a language is of use in the area of the individual. The conditions learning activity to determination of effective for L2 learning are diversified and broadened through language instruction. However, this study focuses modern technology. For example, if there is no fully only on change in literacy and not on the effect that bilingual teacher available, students have alternatives communication in language and different contexts has such as Rosetta Stone, which provide courses for on learners‟ motivation. students to immerse themselves with the target language. In addition, mobile language learning 2.2 L2 Learning Motivation Duolingo claims to provide better learning for free There are many advantages for knowing other because their business model sells translation languages. However, many factors are taking place in services. To give an indication of the growth of the process of successful language acquisition mobile language learning in the past years, a study by (Skehan, 1989; Saville-Troike, 2006). Among all Vavoula (2005) of everyday adult learning for the these factors, maintaining the motivation to learn a MOBIlearn project, based on personal learning second language plays an important role (Gardner, diaries, found that almost half (49%) of the reported 1985; Masgoret & Gardner, 2003; Dörnyei, 2005). learning episodes took place away from home or the learner‟s own office, i.e. the learner‟s usual As part of early research, an extensive interview was environment. done with Dr. Federicon Gobbo, professor in Interlinguistics and Esperanto at the University of The process of memory within language learning is Amsterdam. Gobbo states that if the motivation of a very important in order to increase the language level. language learning falls down, it falls at the beginning The Levels of Processing Theory (Craik, 2002) states 2 of the learning process . that a memory trace can persist in long term memory (LTM) if it involves a deeper level of processing. Motivation has a significant effect on the areas of Therefore, more than one sensory modality, for development and achievement (Steinmayr & Spinath, instance, verbal and visual processing together, are 2009). Motivation clarifies why people choose a needed (Mayer, 2009). particular activity, how long they are willing to continue doing it and what effort they put in to it 2.1.1 Contextual Learning (Dörnyei and Schmidt, 2001). According to Gardner The contextual surroundings of action have a strong (1985) motivation is a “mental engine that subsumes motivational influence on educational language effort, want/will and task enjoyment”. This definition motivation (Dörnyei, 2003). Interesting here are both of motivation will be used as a basis for this study. the context and engagement with the language that influences learning. Learning a language involves the social patterns and acquisition of skills which are 2 Source: Interview with Federico Gobbo distinctive of another community (Gardner, 1985). Overall, there are two types of motivation: performances can positively influence self- intrinsic motivation applies to cases when conficence. language is learned as a desire to integrate into the target language community; 2.3 L2 Learning Motivation Frameworks extrinsic motivation refers to cases where Research on language learning motivation has a long language is learned
Recommended publications
  • Neuro Informatics 2020
    Neuro Informatics 2019 September 1-2 Warsaw, Poland PROGRAM BOOK What is INCF? About INCF INCF is an international organization launched in 2005, following a proposal from the Global Science Forum of the OECD to establish international coordination and collaborative informatics infrastructure for neuroscience. INCF is hosted by Karolinska Institutet and the Royal Institute of Technology in Stockholm, Sweden. INCF currently has Governing and Associate Nodes spanning 4 continents, with an extended network comprising organizations, individual researchers, industry, and publishers. INCF promotes the implementation of neuroinformatics and aims to advance data reuse and reproducibility in global brain research by: • developing and endorsing community standards and best practices • leading the development and provision of training and educational resources in neuroinformatics • promoting open science and the sharing of data and other resources • partnering with international stakeholders to promote neuroinformatics at global, national and local levels • engaging scientific, clinical, technical, industry, and funding partners in colla- borative, community-driven projects INCF supports the FAIR (Findable Accessible Interoperable Reusable) principles, and strives to implement them across all deliverables and activities. Learn more: incf.org neuroinformatics2019.org 2 Welcome Welcome to the 12th INCF Congress in Warsaw! It makes me very happy that a decade after the 2nd INCF Congress in Plzen, Czech Republic took place, for the second time in Central Europe, the meeting comes to Warsaw. The global neuroinformatics scenery has changed dramatically over these years. With the European Human Brain Project, the US BRAIN Initiative, Japanese Brain/ MINDS initiative, and many others world-wide, neuroinformatics is alive more than ever, responding to the demands set forth by the modern brain studies.
    [Show full text]
  • Three Directions for the Design of Human-Centered Machine Translation
    Three Directions for the Design of Human-Centered Machine Translation Samantha Robertson Wesley Hanwen Deng University of California, Berkeley University of California, Berkeley samantha [email protected] [email protected] Timnit Gebru Margaret Mitchell Daniel J. Liebling Black in AI [email protected] Google [email protected] [email protected] Michal Lahav Katherine Heller Mark D´ıaz Google Google Google [email protected] [email protected] [email protected] Samy Bengio Niloufar Salehi Google University of California, Berkeley [email protected] [email protected] Abstract As people all over the world adopt machine translation (MT) to communicate across lan- guages, there is increased need for affordances that aid users in understanding when to rely on automated translations. Identifying the in- formation and interactions that will most help users meet their translation needs is an open area of research at the intersection of Human- Computer Interaction (HCI) and Natural Lan- guage Processing (NLP). This paper advances Figure 1: TranslatorBot mediates interlingual dialog us- work in this area by drawing on a survey of ing machine translation. The system provides extra sup- users’ strategies in assessing translations. We port for users, for example, by suggesting simpler input identify three directions for the design of trans- text. lation systems that support more reliable and effective use of machine translation: helping users craft good inputs, helping users under- what kinds of information or interactions would stand translations, and expanding interactiv- best support user needs (Doshi-Velez and Kim, ity and adaptivity. We describe how these 2017; Miller, 2019). For instance, users may be can be introduced in current MT systems and more invested in knowing when they can rely on an highlight open questions for HCI and NLP re- AI system and when it may be making a mistake, search.
    [Show full text]
  • The MT Developer/Provider and the Global Corporation
    The MT developer/provider and the global corporation Terence Lewis1 & Rudolf M.Meier2 1 Hook & Hatton Ltd, 2 Siemens Nederland N.V. [email protected], [email protected] Abstract. This paper describes the collaboration between MT developer/service provider, Terence Lewis (Hook & Hatton Ltd) and the Translation Office of Siemens Nederland N.V. (Siemens Netherlands). It involves the use of the developer’s Dutch-English MT software to translate technical documentation for divisions of the Siemens Group and for external customers. The use of this language technology has resulted in significant cost savings for Siemens Netherlands. The authors note the evolution of an ‘MT culture’ among their regu- lar users. 1. Introduction 2. The Developer’s perspective In 2002 Siemens Netherlands and Hook & Hat- Under the current arrangement, the Developer ton Ltd signed an exclusive agreement on the (working from home in the United Kingdom) marketing of Dutch-English MT services in the currently acts as the sole operator of an Auto- Netherlands. This agreement set the seal on an matic Translation Environment (Trasy), process- informal partnership that had evolved over the ing documents forwarded by e-mail by the Trans- preceding six-seven years between Siemens and lation Office of Siemens Netherlands in The the Developer (Terence Lewis, trading through Hague. Ideally, these documents are in MS Word the private company Hook & Hatton Ltd). Un- or rtf format, but the Translation Office also re- der the contract, Siemens Netherlands under- ceives pdf files or OCR output files for automatic takes to market the MT Services provided by translation.
    [Show full text]
  • TAUS Speech-To-Speech Translation Technology Report March 2017
    TAUS Speech-to-Speech Translation Technology Report March 2017 1 Authors: Mark Seligman, Alex Waibel, and Andrew Joscelyne Contributor: Anne Stoker COPYRIGHT © TAUS 2017 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system of any nature, or transmit- ted or made available in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior written permission of TAUS. TAUS will pursue copyright infringements. In spite of careful preparation and editing, this publication may contain errors and imperfections. Au- thors, editors, and TAUS do not accept responsibility for the consequences that may result thereof. Design: Anne-Maj van der Meer Published by TAUS BV, De Rijp, The Netherlands For further information, please email [email protected] 2 Table of Contents Introduction 4 A Note on Terminology 5 Past 6 Orientation: Speech Translation Issues 6 Present 17 Interviews 19 Future 42 Development of Current Trends 43 New Technology: The Neural Paradigm 48 References 51 Appendix: Survey Results 55 About the Authors 56 3 Introduction The dream of automatic speech-to-speech devices enabling on-the-spot exchanges using translation (S2ST), like that of automated trans- voice or text via smartphones – has helped lation in general, goes back to the origins of promote the vision of natural communication computing in the 1950s. Portable speech trans- on a globally connected planet: the ability to lation devices have been variously imagined speak to someone (or to a robot/chatbot) in as Star Trek’s “universal translator” to negoti- your language and be immediately understood ate extraterrestrial tongues, Douglas Adams’ in a foreign language.
    [Show full text]
  • Translation Technology Landscape Report
    Translation Technology Landscape Report April 2013 Funded by LT-Innovate Copyright © TAUS 2013 1 Translation Technology Landscape Report COPYRIGHT © TAUS 2013 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system of any nature, or transmitted or made available in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior written permission of TAUS. TAUS will pursue copyright infringements. In spite of careful preparation and editing, this publication may contain errors and imperfections. Authors, editors, and TAUS do not accept responsibility for the consequences that may result thereof. Published by TAUS BV, De Rijp, The Netherlands. For further information, please email [email protected] 2 Copyright © TAUS 2013 Translation Technology Landscape Report Target Audience Any individual interested in the business of translation will gain from this report. The report will help beginners to understand the main uses for different types of translation technology, differentiate offerings and make informed decisions. For more experienced users and business decision-makers, the report shares insights on key trends, future prospects and areas of uncertainty. ,QYHVWRUVDQGSROLF\PDNHUVZLOOEHQH¿WIURPDQDO\VHVRIXQGHUO\LQJYDOXH propositions. Report Structure This report has been structured in discrete chapters and sections so that the reader can consume the information needed. The report does not need to be read from VWDUWWR¿QLVK7KHFRQYHQLHQFHDIIRUGHGIURPVXFKDVWUXFWXUHDOVRPHDQVWKHUHLV some repetition. Authors: Rahzeb Choudhury and Brian McConnell Reviewers - Jaap van der Meer and Rose Lockwood Our thanks to LT-Innovative for funding this report. Copyright © TAUS 2013 3 Translation Technology Landscape Report CONTENTS 1. Translation Technology Landscape in a Snapshot 8 2.
    [Show full text]
  • Download Your FREE Copy of the LT2013
    THE FORUM FOR EUROPE'S LANGUAGE TECHNOLOGY INDUSTRY Language Technologies LT2013: Status and Potential of the European Language Technology Markets March 2013 www.lt‐innovate.eu ‐ contact@lt‐innovate.eu www.lt‐innovate.eu ‐ contact@lt‐innovate.eu TABLE OF CONTENTS Table of Contents .....................................................................................................................................1 Executive Summary ..................................................................................................................................2 Key Extracts....................................................................................................................................3 1. A New ICT Ecosystem ...........................................................................................................................6 1.1 The deep transformation of the competitive landscape .........................................................6 1.2 A Mobile/Social/Global Ecosystem ..........................................................................................7 2. Markets for Language Technology ......................................................................................................11 2.1 The Market Context for LT ......................................................................................................11 2.2 The LT‐Innovate Market Model ...............................................................................................14 2.3 Trends & Growth by Segment.................................................................................................17
    [Show full text]
  • Problem Solving Activities in Post-Editing and Translation from Scratch a Multi-Method Study
    Problem solving activities in post-editing and translation from scratch A multi-method study Jean Nitzke language Translation and Multilingual Natural science press Language Processing 12 Translation and Multilingual Natural Language Processing Editors: Oliver Czulo (Universität Leipzig), Silvia Hansen-Schirra (Johannes Gutenberg-Universität Mainz), Reinhard Rapp (Johannes Gutenberg-Universität Mainz, Hochschule Magdeburg-Stendal) In this series: 1. Fantinuoli, Claudio & Federico Zanettin (eds.). New directions in corpus-based translation studies. 2. Hansen-Schirra, Silvia & Sambor Grucza (eds.). Eyetracking and Applied Linguistics. 3. Neumann, Stella, Oliver Čulo & Silvia Hansen-Schirra (eds.). Annotation, exploitation and evaluation of parallel corpora: TC3 I. 4. Czulo, Oliver & Silvia Hansen-Schirra (eds.). Crossroads between Contrastive Linguistics, Translation Studies and Machine Translation: TC3 II. 5. Rehm, Georg, Felix Sasaki, Daniel Stein & Andreas Witt (eds.). Language technologies for a multilingual Europe: TC3 III. 6. Menzel, Katrin, Ekaterina Lapshinova-Koltunski & Kerstin Anna Kunz (eds.). New perspectives on cohesion and coherence: Implications for translation. 7. Hansen-Schirra, Silvia, Oliver Czulo & Sascha Hofmann (eds). Empirical modelling of translation and interpreting. 8. Svoboda, Tomáš, Łucja Biel & Krzysztof Łoboda (eds.). Quality aspects in institutional translation. 9. Fox, Wendy. Can integrated titles improve the viewing experience? Investigating the impact of subtitling on the reception and enjoyment of film using eye tracking and questionnaire data. 10. Moran, Steven & Michael Cysouw. The Unicode cookbook for linguists: Managing writing systems using orthography profiles. 11. Fantinuoli, Claudio (ed.). Interpreting and technology. 12. Nitzke, Jean. Problem solving activities in post-editing and translation from scratch: A multi-method study. ISSN: 2364-8899 Problem solving activities in post-editing and translation from scratch A multi-method study Jean Nitzke language science press Nitzke, Jean.
    [Show full text]
  • A Retrospective and Prospective View Of
    A retrospective and prospective view of translation research from an empirical, experimental, and cognitive perspective: The International Journal for Translation & Interpreting Research the TREC network trans-int.org Amparo Hurtado Albir Universitat Autònoma de Barcelona [email protected] Fabio Alves Universidade Federal de Minas Gerais [email protected] Birgitta Englund Dimitrova Stockholms Universitet [email protected] Isabel Lacruz Kent State University [email protected] DOI: ti.106201.2015.a02 Abstract. The aim of this paper is to discuss some developments in empirical translation research with an experimental and cognitive perspective. The focus is on the activities and research of the network TREC (Translation, Research, Empiricism, Cognition). The network was formed in 2011, funded by the Spanish Ministry of Economy and Competitiveness and led by PACTE (Universitat Autònoma de Barcelona). It consists of translation scholars and research groups united by their common interest in empirical and experimental research, particularly in relation to the cognitive operations that underlie the task of translating. The paper first gives a short general overview of research on translation as a cognitive activity and outlines the objectives of the TREC network. The network members, representing universities from Argentina, Brazil, Denmark, Finland, Ireland, Norway, Spain, Sweden, Switzerland, the UK, and the USA, then present their most important contributions to cognitively oriented research (topics, methods, results). Finally, some conclusions are drawn and perspectives for future research are outlined. Keywords: translation, cognition, empirical-experimental research, process-oriented translation studies, networking 1. Research on translation as a cognitive activity Studies concerning translation as a cognitive activity date back to the late 1960s.
    [Show full text]
  • A Linguistics Study of New Trends in Translation As a Speech to Act
    International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 Index Copernicus Value (2013): 6.14 | Impact Factor (2013): 4.438 A Linguistics Study of New Trends in Translation as a Speech to Act Riyad Sarhan Jabbar Faculty of Education, University of Kufa, Najaf, Iraq, P. O. Box 21 Abstract: Machine translation is the only available alternative to human translation. Thus, evaluating machine translation software, is very important to improve the performance of these software. This study aims to highlight the difference between human translation and machine translation with reference to speech to text program . In this study , the approaches of translation are mentioned as direct approach , interlingua approach , and the transfer approach . The problem of this program is with the literary translation more than the other types of translation as scientific and idioms . The most accurate is the scientific one as this study proves . As a solution to overcome the problem of literary translation is that machine translation software should be modified and updated continuously , so that they can keep pace with the follow of literary terms . Also , the study shows the advantages and disadvantages of using machine translation. Moreover, the work illustrates the types of linguistic problems encountered in machine translation, and some solutions to overcome these problems. Keywords: Translation, Machine Translation, Translation software, speech, Text, Transfer approach, Interlingua approach 1. Introduction 1.2 The Aims of the Study 1.1 The Problems of the Study 1) The study will attempt to come out with some solutions to machine translation (MT) problem whenever possible The mechanization of translation it has been one of so as to come with highly quality automatic translation .
    [Show full text]
  • Automatic Text Extraction and Translation
    Image-Based Mobile Service: Automatic Text Extraction and Translation J´erˆome Berclaza, Nina Bhattib,StevenJ.Simskec and John C. Schettinob a CVLab, EPFL, Lausanne, Switzerland b HP Labs, Palo Alto, CA, USA c HP Labs, Fort Collins, CO, USA ABSTRACT We present a new mobile service for the translation of text from images taken by consumer-grade cell-phone cameras. Such capability represents a new paradigm for users where a simple image provides the basis for a service. The ubiquity and ease of use of cell-phone cameras enables acquisition and transmission of images anywhere and at any time a user wishes, delivering rapid and accurate translation over the phone’s MMS and SMS facilities. Target text is extracted com- pletely automatically, requiring no bounding box delineation or related user intervention. The service uses localization, binarization, text deskewing, and optical character recognition (OCR) in its analysis. Once the text is translated, an SMS message is sent to the user with the result. Further novelties include that no software installation is required on the handset, any service provider or camera phone can be used, and the entire service is implemented on the server side. Keywords: Scene text extraction, mobile phone camera, client / server, translation 1. INTRODUCTION Imagine a traveler dining in a restaurant in a country on the other side of the world and struggling with the menu. “Is it Beef Steak or Lizard Steak?” could be one of the more pressing questions as the traveler reads through the menu. What if this traveler could use her camera phone to get a translation simply by taking a picture of the menu, sending a MMS and promptly receiving an SMS with the answer? In this paper we describe such a system that uses any camera phone and any mobile service provider to accomplish this task quickly and easily.
    [Show full text]
  • Trkic G00gle: Why and How Users Game Translation Algorithms
    Trkic G00gle: Why and How Users Game Translation Algorithms SOOMIN KIM, Seoul National University, South Korea CHANGHOON OH, Boston College, USA WON IK CHO, Seoul National University, South Korea DONGHOON SHIN, Seoul National University, South Korea BONGWON SUH, Seoul National University, South Korea JOONHWAN LEE∗, Seoul National University, South Korea Individuals interact with algorithms in various ways. Users even game and circumvent algorithms so as to achieve favorable outcomes. This study aims to come to an understanding of how various stakeholders interact with each other in tricking algorithms, with a focus towards online review communities. We employed a mixed-method approach in order to explore how and why users write machine non-translatable reviews as well as how those encrypted messages are perceived by those receiving them. We found that users are able to find tactics to trick the algorithms in order to avoid censoring, to mitigate interpersonal burden, toprotect privacy, and to provide authentic information for enabling the formation of informative review communities. They apply several linguistic and social strategies in this regard. Furthermore, users perceive encrypted messages as both more trustworthy and authentic. Based on these findings, we discuss implications for online review community and content moderation algorithms. CCS Concepts: • Human-centered computing ! User studies. Additional Key Words and Phrases: Human-AI Interaction; algorithmic experience; gaming; translation algorithm; online review; recommendation algorithm; peer-to-peer platform ACM Reference Format: Soomin Kim, Changhoon Oh, Won Ik Cho, Donghoon Shin, Bongwon Suh, and Joonhwan Lee. 2021. Trkic G00gle: Why and How Users Game Translation Algorithms. Proc. ACM Hum.-Comput. Interact.
    [Show full text]
  • Unmet Needs and Opportunities for Mobile Translation AI Daniel J
    Unmet Needs and Opportunities for Mobile Translation AI Daniel J. Liebling, Abigail Evans Aaron Donsbach, Michal Lahav Northeastern University Jess Holbrook, Boris Smus, Google Seattle, WA Lindsey Boran Seattle, WA [email protected] Google dliebling,[email protected] Seattle, WA donsbach,jessh,smus,[email protected] ABSTRACT affordances including speech recognition and augmented real- Translation apps and devices are often presented in the con- ity [14]. text of providing assistance while traveling abroad. However, Access to translation, then, appears to be universally available. the spectrum of needs for cross-language communication is However, little public research exists that details people’s trans- much wider. To investigate these needs, we conducted three lation needs and examines how translation apps meet those studies with populations spanning socioeconomic status and needs. For what populations, in which scenarios, and what con- geographic regions: (1) United States-based travelers, (2) mi- tent is translated? How do translation apps succeed or fail at grant workers in India, and (3) immigrant populations in the these tasks? This paper sheds new light on these questions. We United States. We compare frequent travelers’ perception detail the language needs of, and use of translation technology and actual translation needs with those of the two migrant by, three different communities: English-speaking travelers communities. The latter two, with low language proficiency, based in the United States, Hindi-speaking intra-national mi- have the greatest translation needs to navigate their daily lives. grant workers who live in Tamil-speaking Chennai, India, and However, current mobile translation apps do not meet these immigrants with low English proficiency who live in Seattle, needs.
    [Show full text]