Contact
![Contact Camille Dubois](https://cdn.statcdn.com/contactPerson/4039.jpg)
Lun - Ven, 9:00 - 18:00 h (EST)
![Contact Meredith Alda](https://cdn.statcdn.com/contactPerson/3646.jpg)
Lun - Ven, 9:00 - 18:00 h (EST)
![Contact Yolanda Mega](https://cdn.statcdn.com/contactPerson/3195.jpg)
Lun - Ven, 9:00 - 17:00 h (SGT)
![Contact Kisara Mizuno](https://cdn.statcdn.com/contactPerson/2661.jpg)
Lun - Ven, 10:00 - 18:00 h (JST)
![Contact Lodovica Biagi](https://cdn.statcdn.com/contactPerson/863.jpg)
Lun - Ven, 9:00 - 18:00 h (GMT)
![Contact Carolina Dulin](https://cdn.statcdn.com/contactPerson/3012.jpg)
Lun - Ven, 9:00 - 18:00 h (EST)
Over the years, language translation and natural language processing (NLP) have witnessed significant advancements that have led to the emergence of current trends in the field. One of these developments is the growing use of neural machine translation (NMT) models, which leverage deep learning techniques and large-scale language datasets to improve translation accuracy and fluency. Another is the integration of NLP with other artificial intelligence technologies, such as speech recognition and image understanding, to enable multimodal translation capabilities that encompass spoken and visual content. A third is the increasing focus on developing more specialized and domain-specific translation models, allowing for accurate and contextually appropriate translations in specialized fields such as medicine, law, and finance.
The growth of the natural language processing (NLP) market is being driven by several factors, including the increasing globalization of businesses and the rise of eCommerce. As businesses expand their operations globally, the need for accurate and efficient translation services becomes critical. Additionally, the demand for multilingual customer support is driving the adoption of language translation NLP in the customer service industry. Lastly, the increasing adoption of machine translation in the healthcare industry to improve communication between healthcare providers and patients who speak different languages will further fuel market growth.
The Language Translation Natural Language Processing (NLP) market is expected to continue its growth trajectory until 2030. The market is expected to grow at a CAGR of 13.5% from 2023 to 2030.
Data coverage: The data encompasses B2B, B2G, and B2C enterprises. Figures are based on the funding values from different industries for the market.
Modeling approach / Market size:Market sizes are determined through a top-down approach with a bottom-up validation, building on a specific rationale for each market. As a basis for evaluating markets, we use annual financial reports, funding data, and third-party data. In addition, we use relevant key market indicators and data from country-specific associations such as GDP, number of internet users, number of secure internet servers, and internet penetration. This data helps us estimate the market size for each country individually.
Forecasts:In our forecasts, we apply diverse forecasting techniques. The selection of forecasting techniques is based on the behavior of the relevant market. For example, the S-curve function and exponential trend smoothing are well suited to forecast digital products and services due to the non-linear growth of technology adoption. The main drivers are the level of digitalization, the number of secure internet servers, and the revenue of the Public Cloud market.
Additional Notes: The data is modeled using current exchange rates. The impact of the COVID-19 pandemic and the Russian-Ukraine war are considered at a country-specific level. The market is updated twice a year. In some cases, the market is updated on an ad-hoc basis (e.g., when new, relevant data has been released or significant changes within the market have an impact on the projected development). Data from the Statista Consumer Insights Global survey is weighted for representativeness.
Lun - Ven, 9:00 - 18:00 h (EST)
Lun - Ven, 9:00 - 18:00 h (EST)
Lun - Ven, 9:00 - 17:00 h (SGT)
Lun - Ven, 10:00 - 18:00 h (JST)
Lun - Ven, 9:00 - 18:00 h (GMT)
Lun - Ven, 9:00 - 18:00 h (EST)