Global Machine Translation Market Research Report 2023-Competitive Analysis, Status and Outlook by Type, Downstream Industry, and Geography, Forecast to 2029

Global Machine Translation Market Research Report 2023-Competitive Analysis, Status and Outlook by Type, Downstream Industry, and Geography, Forecast to 2029

Machine translation (MT) is automated translation. It is the process by which computer software is used to translate a text, speech and image files from one natural language to another. MT tools are often used to translate vast amounts of information involving millions of words that could not possibly be translated the traditional way. The quality of MT output can vary considerably; MT systems require “training” in the desired domain and language pair to increase quality.

Market Overview:

The latest research study on the global Machine Translation market finds that the global Machine Translation market reached a value of USD 978.96 million in 2022. It’s expected that the market will achieve USD 2100.37 million by 2028, exhibiting a CAGR of 13.57% during the forecast period.

Influence of COVID-19 Outbreak on Machine Translation Industry Development

Machine translation enables low-cost communication between different languages in different countries around the world, and its main advantages are as follows.
Low cost. The cost of machine translation is much lower as compared to human translation. Machine translation requires very little human participation in the process, and basically the computer completes the translation automatically, which greatly reduces the translation cost.
Easy to control. The process of machine translation is simple and fast, and the control of translation time can also be more accurate estimation.
Fast speed. The computer program runs very fast, and its speed is incomparable to the speed of manual translation.
Due to these advantages, machine translation has developed rapidly over the decades.

The introduction of deep learning has transformed the field of machine translation, significantly improving the quality of machine translation and making it possible to commercialize machine translation. Machine translation is reborn under the effect of deep learning, and with the continuous improvement of the accuracy of translation results, machine translation products are expected to expand a broader market.

During the period of COVID-19, more people are being infected and dying from exposure to the virus. Some countries in Europe, such as Spain, France, the United Kingdom and Italy, are particularly affected by this virus. Health professionals and the public are eager for up-to-date information about the effects of the virus and the treatments that have been proven effective. If language is a barrier to accessing relevant information, machine translation (MT) can help people assimilate information published in different languages.

Although the percentage of machine translation applied to the healthcare sector increased considerably during COVID-19. However, the global manufacturing industry suffered a huge blow due to other negative effects of the pandemic. The impact of the epidemic on the manufacturing industry will involve all major links and all entities in the industry chain. In order to avoid large-scale population movements and gatherings, various countries have adopted prevention and control measures such as home isolation. More and more cities adopted strictly isolating measures, strictly prohibiting vehicle entry and exit, strictly controlling the flow of personnel, and strictly preventing the spread of the epidemic. This makes it impossible for non-local employees to return or arrive immediately, the number of employees is insufficient, and normal commuting is also severely frustrated, resulting in a large-scale shutdown of production. The existing raw and auxiliary material reserves cannot meet the needs of normal production, and the raw material inventory of most companies cannot maintain production. The industry's start-up load dropped again and again, and market sales dropped sharply.

Region Overview:

From 2023-2028, North America is estimated to witness robust growth prospects.

Company Overview:

RWS Holdings PLC is one of the major players operating in the Machine Translation market, holding a share of 5.68% in 2020.

RWS has established itself as the world leader in translation and localization, intellectual property support solutions and life sciences language services.

Through organic growth and strategic acquisitions, the company has developed four dedicated divisions providing translation, patent filing, search and language services to a global client base across all industries.

SDL is the intelligent language and content company. SDL operates across a wide range of sectors including those with high-value content needs within regulatory environments, or those requiring highly specialist or revenue-generating content. These sectors include Financial Services, Life Sciences, Legal, Aerospace and Defense, and Marketing Solutions.

Segmentation Overview:

Among different product types, On-Premise segment is anticipated to contribute the largest market share in 2028.

Application Overview:

By application, the Military and Defense segment occupied the biggest share from 2018 to 2022.

Key Companies in the global Machine Translation market covered in Chapter 3:

IBM Corporation
Lionbridge Technologies Inc.
Microsoft Corporation
Smart Communications Inc.
Google LLC
Systran International Co. Ltd.
Yandex N.V.
Omniscien Technologies Inc.
Cloudwords Inc.
Lingotek Inc.
AppTek Partners LLC
PROMT Ltd
SDL PLC
Welocalize Inc.
RWS Holdings PLC

In Chapter 4 and Chapter 14.2, on the basis of types, the Machine Translation market from 2018 to 2029 is primarily split into:

On-Premise
Cloud-based

In Chapter 5 and Chapter 14.3, on the basis of Downstream Industry, the Machine Translation market from 2018 to 2029 covers:

Automotive
Military and Defense
Healthcare
IT
Electronics
E-commerce
Others

Geographically, the detailed analysis of consumption, revenue, market share and growth rate, historic and forecast (2018-2029) of the following regions are covered in Chapter 8 to Chapter 14:

North America (United States, Canada)
Europe (Germany, UK, France, Italy, Spain, Russia, Netherlands, Turkey, Switzerland, Sweden)
Asia Pacific (China, Japan, South Korea, Australia, India, Indonesia, Philippines, Malaysia)
Latin America (Brazil, Mexico, Argentina)
Middle East & Africa (Saudi Arabia, UAE, Egypt, South Africa)