National Academies Press: OpenBook

Japanese to English Machine Translation: Report of a Symposium (1990)

Chapter: 1. Machine Translation: From a Translation to a Communications and Information Challenge

« Previous: Contents
Suggested Citation:"1. Machine Translation: From a Translation to a Communications and Information Challenge." National Research Council. 1990. Japanese to English Machine Translation: Report of a Symposium. Washington, DC: The National Academies Press. doi: 10.17226/9512.
×
Page 1
Suggested Citation:"1. Machine Translation: From a Translation to a Communications and Information Challenge." National Research Council. 1990. Japanese to English Machine Translation: Report of a Symposium. Washington, DC: The National Academies Press. doi: 10.17226/9512.
×
Page 2
Suggested Citation:"1. Machine Translation: From a Translation to a Communications and Information Challenge." National Research Council. 1990. Japanese to English Machine Translation: Report of a Symposium. Washington, DC: The National Academies Press. doi: 10.17226/9512.
×
Page 3
Suggested Citation:"1. Machine Translation: From a Translation to a Communications and Information Challenge." National Research Council. 1990. Japanese to English Machine Translation: Report of a Symposium. Washington, DC: The National Academies Press. doi: 10.17226/9512.
×
Page 4
Suggested Citation:"1. Machine Translation: From a Translation to a Communications and Information Challenge." National Research Council. 1990. Japanese to English Machine Translation: Report of a Symposium. Washington, DC: The National Academies Press. doi: 10.17226/9512.
×
Page 5
Suggested Citation:"1. Machine Translation: From a Translation to a Communications and Information Challenge." National Research Council. 1990. Japanese to English Machine Translation: Report of a Symposium. Washington, DC: The National Academies Press. doi: 10.17226/9512.
×
Page 6
Suggested Citation:"1. Machine Translation: From a Translation to a Communications and Information Challenge." National Research Council. 1990. Japanese to English Machine Translation: Report of a Symposium. Washington, DC: The National Academies Press. doi: 10.17226/9512.
×
Page 7

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Machine Translation: From a Translation to a Communications and Information Challenge - Developmental work on machine translation has been under way for more than 30 years. Some say that we have come a long way, while others question whether the goal is in sight. The reality is that perceptions of what machine translation is-its purpose and scope are shifting. The paradigm that dominated thinking during most of this 30-year period of research and development (R&D) was the expectation Mat computer technologies could be developed to build machines capable of doing the work of human translators. Today, machine translation~efined as translation generated by a computer, with or without human intervention~mbraces a broad spectrum of technologies. Included are machine translation systems that run on large mainframes and those that run on stand-alone personal computers, enhanced with automatic aids for the human translator.! Rather than eliminating human translators, machine translation and related technologies are now seen as ways of facilitating their work.2 The focus of the symposium organized by the Office of Japan Affairs and the Computer Science and Technology Board was machine translation from Japanese to English. Growing interest in machine translation between this language pair I This report deals with computer-based translation, including machine translation systems and machine aids for translators. 2 The concept includes machine translation systems that are used primarily for information scanning, where little or no post-editing is done. Such a system can in some circumstances serve as a mechanical translator for a monolingual researcher. Some of the commercial systems available today are beginning to see this kind of usage in limited circumstances. 1

2 reflects recognition of the importance of science and technology information produced-in Japan. In order to understand the special challenges of Japanese to English machine translation, a comparatively new field of R&D, it is important to appreciate efforts in machine translation involving other languages. CHANGING CONTEXT FOR MACHINE TRANSLATION Machine translation technology development has taken on broader significance in an age of rapid international communication and intense market competition. Competition for global markets has intensified the need for companies to get their messages across to overseas customers who speak foreign languages. Companies doing business around the world must be able to speak the languages of their customers. Some large companies have targeted translation technologies as a component of their competitive strategies: IBM sees translation as a "eating" items for its marketing objectives in the 1990s; Xerox emphasizes the importance of machine translation in launching products simultaneously in multiple markets. As the importance of global markets grows and cycle times shorten for the introduction of new products, translation increasingly becomes an expensive bottleneck for international companies. Another, related explanation for changes in perspectives on machine translation is the information explosion. More specifically, U.S. businessmen, researchers and product developers, and policymakers need a better understanding of what is going on in Japan, because that country has now joined the ranks of the world's technological leaders. The need for translations of Japanese technical documents is now apparent, but only a minute fraction of our science and technology community can speak and read Japanese. Growing recognition of the importance of technical information produced in Japan has stimulated interest in the role that machine translation might play in making it possible for Americans to access reports of new inventions, products, and financial developments in Japan. Changes in thinking about machine translation also reflect the evolution of new concepts of how machine translation systems might be developed and used. Progress in natural language processing technology, the development of more powerful computers, the increasing availability of large, information-laden dictionary data sets, and advances in some aspects of linguistic theory suggest opportunities for R&D. Translations can be delivered through electronic mail and quickly incorporated in successive editions of technical manuals. Interest in "machine-aided translation" has been spurred by the development of workstations 3 Translation of documents is a prerequisite for entering overseas maricets.

3 with dictionaries and other tools that can be used by professional translators. The expectation that translation machines will replace people has now been transformed into the view that these technologies are tools to enhance the efforts of professional translators, researchers, and secretaries. Today the challenges of machine translation development illustrate the broader challenges of information technology research, development, and use. Machine translation technologies pose a range of theoretical, software, hardware, and even sociological problems that require integration of technologies and improved interactions among developers and users. For all these reasons, machine translation today is more than a linguistics problem. It is a communications and information challenge that demands a diverse range of expertise and resources. SETTING AND MEETING GOALS FOR MACHINE TRANSLATION DEVELOPMENT The dream that stimulated early R&D efforts was a machine that produces high-quality translations from a wide variety of source texts at low cost. Even the most ardent supporters of machine translation agree that three decades of effort have not produced the breakthroughs necessary to achieve this dream. Why the dream remains unfulfilled is the subject of some disagreement. Viewed from one angle, the failure to achieve the goal is a result of giving up too early. Negative evaluations of machine translation in the 1960s were based on the argument that the understanding of text by computer was too difficult, rendering machine translation infeasible.4 The ALPAC report by the National Research Council concluded that the basic technology for machine translation had not been developed, and recommended a focus on long-term research in computational linguistics and improvement of translation methods. While the report made no recommendations with regard to funding for research and development on machine translation, the overall negative evaluation of the state- of-the-art is now seen by many as a major cause of the subsequent decline in funding for such research in the United States. Between 1960 and 1970, funding for R&D on machine translation declined Tom about $10 million to $1 million. 4 This argument was made by Bar Hillel. lbe ALPAC report written by the Automatic Language Processing Advisory Committee of the National Research Council, entitled Language and Machines: Computers in Translation and Linguistics, is widely seen as the most influential of the studies of machine translation in the 1960s. Published in 1966, the report concluded that the quality of machine translation was poor and cost savings had not been achieved. lbe report analyzed the products of machine translation at U.S. government agencies after development work had been under way for more than ten years.

4 Supporters of machine translation say that we would be closer to the dream if we had not given up so soon.5 Viewed from another perspective, however, the fact that the initial dream has not been fulfilled is no reason to dismiss the promise of machine translation. The machine translation "heaven" of high-quality, low-cost, general-purpose systems is still distant.6 The high-quality systems that exist today are in most cases special-purpose systems working in restricted domains, but none of these are for the translation of Japanese to English. (See Figure 1.) In addition, there are also a number of cost-effective systems that operate in broader domains. Among them, Systran is the only company to have developed a general-purpose commercial system that translates between Japanese and English, as well as 14 other language pairs. A dozen or more prototype machine translation systems have not been able to attain cost effectiveness after a decade of development The process of machine translating from Japanese to English and vice versa is comparatively difficult because of important differences in the structures of the two languages. Typical Japanese text consists of Chinese characters and two different styles of Japanese phonetic symbols. These characters and symbols are written without any spaces between individual words, and phrases are rarely separated by punctuation. Grammatically. Japanese differs from English in that it has no distinction of singular and plural nouns, there are no articles, and the subjects are often omitted. In general, the Japanese sentence puts the verb at the end, and the text preceding the verb is in no particular order and contains many compound clauses. The grammatical structure of Japanese may omit pronouns, subjects, and objects, so that the context must be understood in order to choose among alternative possible interpretations. Because of these and many other characteristics of the language, pre-editing is especially helpful to make the text more Actable for machine translation processing. Most of the Japanese to English systems now in use in Japan succeed because they are limited to particular domains. In the eyes of many, these systems represent a significant step forward, even if they do not fulfill We initial dream. 5 In July 1989 the Japan Electronic Industry Development Association published a report entitled: A Japanese View of Machine Translation in Light of the Considerations and Recommendations Reported by ALPAC, U.S.A. This report argues that two major conclusions of the ALPAC report are no longer valid: the claim that there is no translation shortage is refuted by estimates of today's translation market in Japan, and numerous examples of successful machine translation are also cited in response to ALPAC's conclusion that it will have no practical use in the near future. The Japan Electronic Industry Development Association's Machine Translation System Research Committee, which prepared the report, was chaired by Dr. Makoto Nagao of Kyoto University and included representatives from Japanese corporations involved in machine translation development. 6 Some argue that the major explanation for the failure lo reach the target is that there is a much bigger difference between general language and domain-specific language than has heretofore been suspected.

s High-Qual~y Systems Cost-Effective Systems Prototype Systems Demonstration Systems ,:3 ,:3 ~ NEr )\ E-J J _ _ _ ~( _ /=iN , {~3 ~- · Special Purpose Systems · Interactive Systems . Constrained Systems · Domain- Speafic Systems · General- Purpose Systems FIGURE 1 Machine translation quality/funciion matnx. SOURCE: Bemard Scott, Logos Corporation. See legend on page 6. The argument may be rephrased as follows: Japanese to English machine anslaiion systems can be used effectively for carefully targeted purposes and it will only be possible to improve these systems if we are willing to put resources into development and experimentation. When we also consider the growth of machine aids for human translators, such as dictionaries and other composition tools, it is clear that machine translation technologies have practical uses today, even if the dream of a fully automated, high-quality, low-cost, general-purpose system remains over the horizon. Given this picture of promise and problems associated with machine translation, we need to examine the challenges that lie ahead for U.S. industry and the U.S. government. One set of challenges is commercial and relates to the fact that while a number of Japanese companies are working on Japanese to English machine translation systems, little similar work is going on in the United

6 LEGEND TO FIGURE 1 ALPAC Russian-English machine translation systems being developed under U. S. Department of Defense funding prior to the publication of the ALPAC Report in 1966, which led to their discontinuation. ALPNET Interactive multilingual translation aid, developed in the United States. Previously known as ALPS for Automated Language Processing System. EEC European Economic Community. EUROTRA I Large-scale multilingual machine translation prototype effort sponsored by the European Community. Eurotra I is intended to lead to a full-scale industrialized version, Eurotra II, encompassing 72 language pairs. FTD Russian-English and German-English SYSTRAN-based machine translation systems of the Foreign Technology Division of the U.S. Air Force. FTD's installation in the late 1960's represented the first operational use of machine translation. GETA Machine translation system for various language pairs entailing French, developed at the University of Grenoble, France. (GETA - Groupe d'Etudes pour la lraduct~on Automatique.) LOGOS METAL METEO Multilingual machine translation system developed and marketed by Logos Corporation, a U.S. company. Language pairs are: German-English, -French, -Italian; English-French, -Spanish, -German, and -Italian. German-English, English-German machine translation system originally developed at the Linguistic Research Center of the University of Texas and later under joint development with Siemens AG in Munich. English-French machine translation system developed for the nationwide weather communications network of the Canadian Meteorological Center. METRO is a derivative of the TAUbI system developed at the University of Montreal. PAHO English-Spanish/Spanish-English machine translation systems of the Pan American Health Organization designated as SPANAM and ENGSPAN, respectively. SYSTRAN Machine translation system for many language pairs, developed in the U.S. and controlled by French and Japanese interests. SYSTRAN is a much enhanced derivative of the early Georgetown Automatic Translation (OAT) system. TAUM Aviation An English-French adaptation of TAUM technology to a specific subject matter domain or language subset, developed at the University of MontrEal. (TAUM - Traduction Automatique de l'Universite de Montreal.) J-E/E-J XEROX Japanese-English/English-Japanese machine translation systems. There are about a dozen such systems in Japan, either on the market or being prepared for the market. English-multitarget machine translation system developed for XEROX Corporation by the developers of SYSTRAN, and used by XEROX to translate technical manuals written in controlled English.

7 States. A second set of challenges includes technical problems issues relating to the choice of R&D focus and problems in evaluating system performance. The Bird set of challenges may prove to be the most pressing: defining R&D policy (either at the company or the U.S. government level). Without a clear consensus on what constitutes the '~state-of-the-art," or comprehensive data on market prospects and user needs, forging an appropriate policy response is not an easy task. The sections that follow address each of these three sets of challenges in turn, highlighting areas of uncertainty and issues that deserve further study and debate.

Next: 2. The Commercial Challenges »
Japanese to English Machine Translation: Report of a Symposium Get This Book
×
MyNAP members save 10% online.
Login or Register to save!
  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  6. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  7. ×

    View our suggested citation for this chapter.

    « Back Next »
  8. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!