In the 21st century, emerging digital communication technologies and the World Wide Web facilitated an exponential growth in the volume of information in different languages and blurred geographic boundaries, making once hard-to-find data easily accessible online. Although English was the lingua franca of the Web in its early days, due to rapid information and communication technologies (ICT) growth today less than one-third of Internet users are native English-speakers (Internet World Stats, 2009). There are more than 6,700 languages in the world today (Masci, D., 2000). The growing number of users from non-Anglophone countries creates unappeasable demand for cross-cultural interaction and understanding of online content in the era of globalization that speeds up every aspect of modern social interactions, including consumption of information and communication. This social necessity has spurred demand for instant machine translation services.
The high cost and low speed of professional translating has encouraged innovations and experiments with automated digital translation systems. This emerging digital technology allows translate texts from the source language (original text) into the target language (translation) without human assistance. From consumers’ point of view, machine translation has two main goals: assimilation of information (translation for reading and comprehension of an idea) and dissemination of information (localization of documentation).
The most prominent field for machine translation (MT) in modern world is technical translation that generally implies tough timeframe and big volumes of texts. For example, machine translation is widely adopted by meteorologists for weather forecasts, by hardware and software vendors for technical documentation, by students learning foreign languages and others.
Machine translation as a technology and science is relatively young and interconnected with the development of computer technologies. The new direction of MT – speech-translation – is creating new window of opportunities for technology application. This paper primarily explores the evolution of machine translation of documentation and does not cover speech translation. In our research, we use the three innovation theories to understand the history and current position of the translation technology in postmodernism information society:
– the theory of supervening social necessity by Brian Winston presented in his book “Media technology and society. A history from the telegraph to the Internet” that considers innovation from socio-cultural deterministic point of view,
– the theory of disruptive innovation by Clayton M. Christensen who analyzes innovations in the framework of market competition paradigm in the book “Seeing What’s Next: Using the Theories of Innovation to Predict Industry Change”,
– the theory of hype cycles by Gartner Inc. that characterizes a life cycle of early technology adoption on markets.
The first part of the paper analyzes the origin and development of machine translation in the 20th century from the initial ideas to the first commercial systems in the USA and Europe. It will help to explore the factors leading to the growth of machine translation companies in the past reflecting the transformation of machine translation usage from the assimilation of information to the dissemination application. Next part will examine the growing demand for these services in fields as varied as education and commerce, and describe different social implications in these industries. Finally, we’ll explore the possible future trends of machine translation services in the Internet era, looking at services like Google Translate, YouTube, and try to assess its impact on translation industry.
– Alcina, A. (2008). Translation technologies: Scope, tools and resources. Target: International Journal on Translation Studies, 20(1), 79-102. doi: 10.1075/target.20.1.05alc
– Bielsa, E. (2007). Translation in global news agencies. Target: International Journal on Translation Studies, 19(1), 135-155. Retrieved from IngentaConnect. http://www.ingentaconnect.com/content/jbp/targ/2007/00000019/00000001/art00007
– Christensen, C. M., Anthony, S. D., & Roth, E. A. (2004). Seeing what’s next: Using the theories of innovation to predict industry change. Boston: Harvard Business School Press.
– Dillon, S., & Fraser, J. (2006). Translators and TM: An Investigation of Translators’ Perceptions of Translation Memory Adoption. Machine Translation, 20(2), 67-79. Retrieved from Springer. doi 10.1007/s10590-006-9004-8
– Fulford, H. (2001). Translation Tools: An Exploratory Study of Their Adoption by UK Freelance Translators. Machine Translation, 16(4), 219-232. Retrieved from JSTOR. http://www.jstor.org/stable/40007488
– Gaspari, F. (2007). The Role of Online MT in Webpage Translation. PhD Thesis. The University of Manchester. http://www.localisation.ie/resources/Awards/Theses/F_Gaspari_Thesis.pdf
– Gantz, J.F., Chute, C., Manfrediz, A., Minton, S., Reinsel, D., Schlichting, W. & Toncheva, A. (2008). The Diverse and Exploding Digital Universe. IDC White Paper. Bohn, Germany: IDC. Retrieved from http://www.emc.com/collateral/analyst-reports/diverse-exploding-digital-universe.pdf
– Henke, K. (1990). Facilitating translation of technical information for the international market. In Professional Communication Conference, 1990. IPCC 90. Communication Across the Sea: North American and European Practices, International (pp. 90-94). Presented at the Professional Communication Conference, 1990. IPCC 90. Communication Across the Sea: North American and European Practices, International. Retrieved from doi:10.1109/IPCC.1990.111160
– Hutchins, J. (1995). Machine translation: a brief history. In E. Koerner (Ed.), Concise history of the language sciences: from the Sumerians to the cognitivists. New York: Pergamon. 431-445. Retrieved from http://aymara.org/biblio/mtranslation.pdf
– Hutchins, J. (1998). Milestones in Machine Translation no.2. Warren Weaver’s memorandum 1949. Language Today, 6, 22-23 Retrieved from http://www.hutchinsweb.me.uk/Milestones-2.pdf
– IBM Inc. (1954, January 8). 701 Translator [Press release]. Retrieved from http://www-03.ibm.com/ibm/history/exhibits/701/701_translator.html
– Internet World Stats. (2009). Internet World Users by Language. Retrieved from http://www.internetworldstats.com/stats7.htm
– Locke, W. N. (1955). Speech Typewriters and Translating Machines. PMLA, 70(2), 23-32. Retrieved from JSTOR. http://www.jstor.org.offcampus.lib.washington.edu/stable/2699157
– Masci, D. (2000, November 17). Future of language. CQ Researcher, 10, 929-952. Retrieved from CQ Researcher Online, http://library.cqpress.com.offcampus.lib.washington.edu/cqresearcher/cqresrre2000111700
– Muhammad Raji Zughoul et Awatef Miz’il Abu-Alshaar. (2005). English/Arabic/English machine translation: a historical perspective. Meta: journal des traducteurs / Meta: Translators’ Journal, 50(3), 1022–1041. Retrieved from Erudit database. http://www.erudit.org.offcampus.lib.washington.edu/revue/meta/2005/v50/n3/011612ar.html
– O’Hagan, M., & Ashworth, D. (2002). Translation-Mediated Communication in a Digital World: Facing the Challenges of Globalization and Localization. Multilingual Matters Limited.
– Otterbacher, J. (2007) Adoption of Translation Support Technologies in a Multilingual Work Environment. Lecture Notes in Computer Science. Retrieved from Springer. doi: 10.1007/978-3-540-74000-1
– Niño, A. (2008). Evaluating the use of machine translation post-editing in the foreign language class. Computer Assisted Language Learning, 21(1), 29-49. Retrieved from Taylor & Francis. doi: 10.1080/09588220701865482
– Pope, V. (1987, June 12). Technology (a special report): International — a Tower of Babble. Wall Street Journal (Eastern Edition), p.1. Retrieved from ProQuest Newsstand. doi: 27296812
– Prentice, S., Fenn, J., Davies, J., Jacobs, J., Elliot, B., Smith, D.M., …Bell, T. (2009). Hype Cycle for Human-Computer Interaction. Retrieved from Gartner Inc. doi:G00169594
– Purdue University Online Writing Lab (OWL). (March, 2010). APA Formatting and Style Guide. Retrieved from http://owl.english.purdue.edu/owl/resource/560/01/
– Romaine, M. & Richardson, J. (2009). State of translation industry 2009. MyGengo.com. Retrieved from http://mygengo.com/report/translation-industry-2009
– Stafford, T., Stafford, M., & Schkade, L. (2004). Determining Uses and Gratifications for the Internet. Decision Sciences, 35(2), 259-288. Retrieved from EBSCO. doi:10.1111/j.00117315.2004.02524.x.
– Steding, S. (2009). Machine translation in the German classroom: detection, reaction, prevention. (Report). Die Unterrichtspraxis. Retrieved from IngentaConnect. doi:10.1111/j.1756-1221.2009.00052.x
– Slocum, J. (1985). A survey of machine translation: its history, current status, and future prospects. Comput. Linguist., 11(1), 1-17. Retrieved from the ACM. http://portal.acm.org.offcampus.lib.washington.edu/citation.cfm?id=5616#
– The European Association for Machine Translation (2010). What is Machine Translation? Retrieved from http://www.eamt.org/mt.php
– Tucker, A. B. J. (1984). A perspective on machine translation: theory and practice. Communication of the ACM, 27(4), 322-329. Retrieved from ACM. doi: 10.1145/358027.358035
– Van Slype, G. (1982). Economic aspects of machine translation. In V.Lawson (Eds.), Practical experience of machine translation. North-Holland Publishing Company. 79-93. Retrieved from http://www.mt-archive.info/Aslib-1981-VanSlype.pdf
– Wilks, Y. (2008). Machine translation: its scope and limits. New York: Springer.
– Winston, B. (1998). Media technology and society. A history: from the telegraph to the Internet. London: Routledge.
– Yanishevsky, A. (2009, April). The Emerging role of machine translation. PROMT. Retrieved from http://www.promt.ru/press/pdf/promt_for_multilingual.pdf
– Z Yehoshua Bar-Hillel, & Bar-Hillel, Y. (1951). The present state of research on mechanical translation. American Documentation, 2(4), 229-237. Retrieved from EBSCO. doi: 16879287