Europe machine translation market enhancement in technology sector

The Europe machine translation is projected to witness a substantial growth over the forecast period owing to the growing demand from the language service providers. The increasing adoption of machine translation and speech recognition by the service providers has contributed significantly to the growth of the market.

This is primarily attributed to the support from the EU financed programs. Moreover, Europe has a strong presence in the US as the supplier of translation services to larger clients. There is a strong demand for machine translation from the IT industry that establishes Europe as one of major exporters of the machine translation market.

The governments of EU economies are one of the major stakeholders in the Europe machine translation market. The European Commission (EC) introduced online eTranslation services for civil workers in November 2017. The service is accessible to EC information systems through Advance Passenger Information System (API) along with individual users. In addition, contributions from the European Association for Machine Translation are creating opportunities for professional translators, developers, and researchers to promote and develop such systems.

Based on technology, the Europe machine translation market is projected to witness a strong growth in SMT-based systems. These systems yield results by finding similar patterns. These systems require enormous bilingual texts and work by comparing source content to a database of previous translations. Some of the examples of such systems are open-source Moses system, Google Translate, and Bing Translator. These systems are much more natural when compared with RBMT systems.

The prominent players of the Europe machine translation market are Lionbridge, Sampark, Moravia IT, Lucy Software, Microsoft Corporation, Google Inc., IBM Corporation, and others. Companies are deploying Neural Machine Translation (NMT) in their product offerings for a larger market share. 

For instance, Google and Microsoft are developing solutions to effectively translate documents in different languages. Google’s NMT tool was initially launched in 2016 and is based on artificial neural network to decode the semantic data for multilingual translations.