The Spanish Language in the Digital Age — Executive Summary
During the last 60 years, Europe has become a distinct political and economic structure. Culturally and linguistically it is rich and diverse. However, from Portuguese to Polish and Italian to Icelandic, everyday communication between Europe’s citizens, within business and among politicians is inevitably confronted with language barriers. The EU's institutions spend about a billion euros a year on maintaining their policy of multilingualism, i.e., translating texts and interpreting spoken communication. Does this have to be such a burden? Language technology and linguistic research can make a significant contribution to removing the linguistic borders. Combined with intelligent devices and applications, language technology will help Europeans talk and do business together even if they do not speak a common language.
Language barriers can bring business to a halt, especially for SMEs who do not have the financial means to reverse the situation. The only (unthinkable) alternative to this kind of a multilingual Europe would be to allow a single language to take a dominant position, to replace all other languages. Yet without technological support, mastering the 23 official languages of the member states of the European Union and some 60 other European languages is an insurmountable obstacle for Europe’s citizens, economy, political debate, and scientific progress.
The solution is to build key enabling technologies: language technologies will offer European stakeholders tremendous advantages, not only within the common European market, but also in trade relations with non-European countries, especially emerging economies. Language technology solutions will eventually serve as a unique bridge between Europe's languages. An indespensable prerequisite for their development is first to carry out a systematic analysis of the linguistic particularities of all European languages, and the current state of language technology support for them.
The automated translation and speech processing tools currently available on the market fall short of the envisaged goals. The dominant actors in the field are primarily privately-owned for-profit enterprises based in Northern America. As early as the late 1970s, the EU realised the profound relevance of language technology as a driver of European unity, and began funding its first research projects, such as EUROTRA. At the same time, national projects were set up that generated valuable results, but never led to a concerted European effort. In contrast to these highly selective funding efforts, other multilingual societies such as India (22 official languages) and South Africa (11 official languages) have set up long-term national programmes for language research and technology development.
The predominant actors in LT today rely on imprecise statistical approaches that do not make use of deeper linguistic methods and knowledge. For example, sentences are often automatically translated by comparing each new sentence against thousands of sentences previously translated by humans. The quality of the output largely depends on the size and quality of the available data. While the automatic translation of simple sentences in languages with sufficient amounts of available textual data can achieve useful results, shallow statistical methods are doomed to fail in the case of languages with a much smaller body of sample data or in the case of sentences with complex, non-repetitive structures. Analysing the deeper structural properties of languages is the only way forward if we want to build applications that perform well across the entire range of European languages.
The European Union is thus funding projects such as EuroMatrix and EuroMatrix+ (since 2006) and iTranslate4 (since 2010), which carry out basic and applied research, and generate resources for establishing high quality language technology solutions for all European languages. European research in the area of language technology has already achieved a number of successes. For example, the translation services of the European Union now use the Moses open-source machine translation software, which has been mainly developed in European research projects. Rather than building on the outcomes of these research projects, Europe has tended to pursue isolated research activities with a less pervasive impact on the market. The economic value of even the earliest efforts can be seen in the number of spin-offs. A company such as Trados, which was founded back in 1984, was sold to the UK-based SDL in 2005.
Drawing on the insights gained so far, today’s hybrid language technology mixing deep processing with statistical methods should be able to bridge the gap between all European languages and beyond. But as this series of white papers shows, there is a dramatic difference between Europe’s member states in terms of both the maturity of the research and in the state of readiness with respect to language solutions. Although the field of language technology has witnessed much progress in the past years for the Spanish language, further research and development is needed before truly effective language technology solutions are ready for everyday use.
META-NET’s vision is high-quality language technology for all languages that supports political and economic unity through cultural diversity. This technology will help tear down existing barriers and build bridges between Europe’s languages. This requires all stakeholders – in politics, research, business, and society – to unite their efforts for the future.
This white paper series complements the other strategic actions taken by META-NET. Up-to-date information such as the current version of the META-NET vision paper or the Strategic Research Agenda (SRA) can be found on the META-NET web site: http://www.meta-net.eu.
