The Machine Translation Market is segmented by Technology (Statistical Machine Translation, Rule-based Machine Translation, Neural Machine Translation), Deployment (On-premise, Cloud), End User (Automotive, Healthcare, Military and Defense, IT, E-commerce), and Geography.
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Scope of the Report
Key Market Trends
TABLE OF CONTENTS
2018 - 2026
Fastest Growing Market:
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The Machine Translation Market was valued at USD 153.8 million in 2020, and it is expected to reach USD 230.67 million by 2026, registering a CAGR of 7.1%, during the period of 2021-2026. The machine translation market is witnessing excess demand due to the increasing use of computer-assisted tools. The necessity to use the technology in favor of the more efficient translation process is, therefore, continuously increasing.
This continuous increase can be attributed to the growth of emerging economies and the internationalization of many businesses that want to provide their content, products, and services in as many languages as possible. This requirement might prompt translation companies to rely increasingly on machine translation as a tool.
Using machine translation technology, the text is translated at increasingly faster speeds. Multiple translation companies use it in order to generate multilingual content. Moreover, this technology increases the productivity of translators when performing translation, localization, and terminology work. Google Translate is among the most used machine translation tools due to how closely it is integrated with the search engine and Android OS. Google Translate supports around 130 languages.
Some of the key factors augmenting the growth of the machine translation market are the increasing demand for content localization and the growing need for cost-effective and high-speed translation. As machine translation applications are achieving significantly higher accuracy levels, they are increasingly getting employed in diverse areas of business, introducing new applications and enhanced machine-learning models.
The automotive, military and defense and healthcare sectors are the primary end-users of machine translation technology. As thousands of languages are used across the world, the military and defense segment demands the quick translation of high-volume content, to communicate with multilingual populations on a real-time basis.
Furthermore, the technology has been gaining appreciation with its usage during the pandemic. For instance, Google AI and ML translation services help health officials communicate with people in languages they understand to disseminate the COVID-19 information. The company intends to reach 51 million migrants in at least 350 languages in the United States alone.
Scope of the Report
Machine translation (MT) refers to fully automated software that can translate source content into target languages. Humans may use MT to help them render text and speech into another language; The MT software may operate without human intervention. MT tools are often used to translate vast amounts of information, involving millions of words that could not be translated the traditional way. The quality of MT output can vary considerably, and MT systems require training in the desired domain and language pair, to increase quality.
By Technology (Qualitative Trend Analysis)
Statistical Machine Translation
Rule-based Machine Translation
Neural Machine Translation
By End User
Military and Defense
Other End Users
Rest of the World
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Key Market Trends
Neural Machine Translation is Expected to Drive the Market Growth
In the past few years, one of the most exciting developments in the automated translation domain has been the development of neural machine translation (NMT). The technology uses large quantities of data fed into an artificial neural network to predict the likelihood of a sequence of words, typically modeling the entire sentences in a single integrated model. The model learns by doing, in other words, artificial translation intelligence.
NMT is also being improved continuously and refined and is anticipated to become even better in the next few years. They are expected to be embedded in the analytics and other software solutions using across the industry that can make use of these solutions even more easily, where the queries can be done in natural language, while the machine answers them. This can significantly cut the cost of organizations adopting them, prompting them to go for these solutions.
Companies are increasing their focus on developing advanced machine translation systems to meet the growing consumer needs. For instance, Lilt Inc. launched an adaptive neural machine translation system to use a real-time feedback loop and artificial intelligence to boost a human translator's productivity. This technology promises to help close the gap between humans and machines, working together toward a future where humans can communicate and obtain information in multiple languages.
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North America to Hold Maximum Market Share
North America is one of the prominent markets for machine translation, owing to its growing demands across the United States' IT sector, which holds majority of the regional market demand. Some of the prominent IT companies across the region are among the primary adopters of this technology to meet global customers' requirements.
The growth across the region is designated by the presence of a large number of service providers and favorable government initiatives. For instance, SMT services offered by Microsoft Corporation and Google Inc., along with their free online engines, have gained increased popularity in the United States. Moreover, the increasing investments and developments in artificial intelligence and machine learning by the technological giants are expected to bolster the North American machine translation market.
The majority of the prominent players operating in the market are from North America, which is one of the significant factors that leverage a substantial share in the region. Some prominent players have collaborated across the North America region to leverage the latest technological advancements that can be implemented in their business model. For instance, Inventus has fully integrated automatic machine translation into its eDiscovery service offerings. Inventus partnered with Iconic Translation Machines Ltd, a leading translations software provider, to deliver Iconic's latest Neural Machine Translation, either on-premise or in the cloud.
A few organizations in the region are focusing on improving technology. For instance, Facebook is focusing on adding considerable resources to machine translation (MT). In addition to enhancing the quality estimation and various other initiatives, Facebook is currently working on two others that share information with the broader open source community, allowing developers to improve the technology.
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The machine translation market is competitive and consists of several major players. In terms of market share, few of the major players, like IBM Corporation, Microsoft Corporation, Lionbridge Technologies Inc., etc., currently dominate the market. However, with the growing innovation in machine translation, most prominent companies are expanding their market presence by securing new contracts, thereby tapping into the new markets. Some of the recent developments in the market are:
March 2020 - The European Commission's automated eTranslation tool was made available to all the region's small and medium-sized enterprises (SMEs). The SMEs can use the eTranslation tool primarily to translate documents or plain text between any of the 24 official European Union languages, as well as Icelandic, Russian, and Norwegian. The service has been made free of charge while guaranteeing the confidentiality and security of all the translated data.
Oct 2019 - SDL, a prominent player in content creation, translation, and delivery, announced the latest version of its SDL Machine Translation (MT), which goes beyond automatic translation, thereby, integrating with multiple platforms and is expected by the company to be a key technology for digital customer experience, eDiscovery, analytics, internal communications, and collaboration.