Press release
Microsoft, Google Profiled In Machine Translation Market 2024 Report - Systran International, IBM, Moravia IT, Lionbridge Technologies
Global machine translation market share was dominated by SMT technology, which contributed over 60% to the revenue in 2016. This is attributed to the rising demand in the commercial space as it can be trained for specific data set and can be used recurrently for a business. Furthermore, the demand for cheap, fast computing hardware has enabled the SMT demand as it aids applications that rely on billions of statistics and large data.
The players operating in the machine translation market include Moravia IT, Lionbridge Technologies Inc., Google, Microsoft, Systran International, and IBM. In October 2016, AppTek LLC and Emergent LLC, announced that they had entered a partnership agreement. The partnership will aid, Emergent LLC to make the AppTek solutions and product catalog available on SEWP, where Emergent?s customers can update their businesses and grow their revenue using with AppTek?s technologies.
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Increasing requirement to localize the rising amount of content in the organizations to eradicate language barriers is driving the machine translation market. The ability to translate different languages according to the customer preferences and lack of existing translators for several specialized fields and language combinations is providing tremendous growth opportunities for the industry.
Players operating in the machine translation market have been increasing their R&D spending to develop cost effective solutions to fulfil customer requirements. For instance, Lionbridge introduced Smart Automated Translation software that quickly translate large volume content with minimum error and at lower costs. Lack of output accuracy and quality provided by the technology is anticipated to inhibit the machine translation market growth. Machines or software sometime fails to translate content with great accuracy. Such mistakes sometimes prove to be very costly and may hamper the overall business growth.
Growing demand across businesses to implement a cost-effective translation system in their business process is anticipated to drive the adoption rate of machine translation market size over the forecast timeframe. Implementation cost of these services is lower than traditional alternative. In addition to being-cost effective in nature, the technology is capable of performing at much faster speeds than human translators.
The U.S. machine translation market is set to be driven by the presence of a large number of service providers in the region. The support from governmental organizations such as the Defense Advanced Research Projects Agency (DARPA) provides extensive funding for MT for military & defense industry. In addition, the organization has Spoken Language Communication and Translation System for Tactical Use (TRANSTAC) program aimed at evolving transportable two-way speech translation systems that can operate on handheld and laptop devices.
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The machine translation market size is primarily driven by the rising demand for automated translations to eliminate repetitive tasks and the escalating need for localization to better serve the customers by the companies. In addition, several companies are deploying the technology to deliver multilingual content for their global website.
Automotive applications will witness considerable growth due to the increasing use of the technology in efficiently interpreting motor part catalogs, technical documentation, how-to manuals, and automotive websites, such as Chrome Data. This way the machine translation market aids the OEMs in quickening entry into international markets and surge revenue and brand equity.
Complete report for 2017-2024 on Machine Translation market is now available at https://www.marketstudyreport.com/reports/machine-translation-market
Related Report:
Machine Translation Market Growth Potential, Price Trends, Competitive Market Share & Forecast, 2017 - 2024
Global Machine Translation Market 2017 by Manufacturers, Countries, Type and Application, Forecast to 2024 to its research database. This research study is segmented on the bases of applications, technology, geography and types.
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