AI Translation Market is Booming Worldwide | DeepL, Systran, SDL, Prompsit
Updated · Jun 26, 2023
Published Via 11Press : According to HTF MI, The report “Global AI Translation Market: Industry Trends, Share, Size, Growth, Opportunity, and Forecast 2023-2029” is available for purchase. From 2023 to 2028, the Global AI Translation Market is expected to develop at a compound annual growth rate (CAGR) of 5.7%, reaching USD 650.8 Million in 2023 and USD 3520.9 Million by 2028.
AI Translation, often known as machine translation, is a game-changing technology that is transforming digital language communication. AI translation, which is powered by powerful artificial intelligence algorithms, allows for the automatic conversion of text or speech from one language to another with exceptional accuracy and speed. AI translation systems learn patterns, grammatical rules, and contextual signals to create high-quality translations by analyzing massive volumes of language data. These systems use neural networks and deep learning techniques to analyze the content and purpose of the original text, resulting in increasingly fluent and natural-sounding translations.
AI translation has far-reaching ramifications for a wide range of sectors and worldwide communication. It allows for seamless multilingual communication, removing language barriers in fields such as commerce, education, tourism, and diplomacy. AI translation improves efficiency and productivity in content localization by processing massive amounts of content fast, allowing organizations to expand their reach and interact with worldwide audiences. While AI translation progresses, it is critical to recognize the necessity for human intervention to ensure accuracy and cultural sensitivity. The future of translation holds enormous promise for enhancing global understanding and collaboration by combining the strengths of AI and human knowledge.
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Key and Developing Players,
- Lucy Software
- Iconic Translation Machines
- As global enterprises expand, there is a greater need for effective communication across several languages, fueling demand for AI translation solutions.
- Because of the expansion of digital material in numerous formats, including websites, social media, and documents, automated translation systems are required to manage enormous amounts efficiently.
- When compared to traditional human translation, AI translation offers faster and more cost-effective translation, leading to greater use by organizations seeking to minimize translation prices and turnaround times.
- Because of its capacity to provide more fluent and contextually correct translations, neural machine translation has gained significant popularity in recent years.
- Manufacturers are increasingly relying on NMT algorithms to provide AI translation solutions that perform better.
- The rise of cloud computing has facilitated the creation of cloud-based translation systems that provide scalable and on-demand translation services.
- This trend allows manufacturers to provide AI translation as a service, allowing them to access a wider market.
- AI translation is being combined with other developing technologies such as natural language processing (NLP), speech recognition, and chatbots to provide more comprehensive language solutions for a variety of applications.
- Manufacturers can benefit from building AI translation systems specialized to certain businesses or sectors, such as e-commerce, travel and hospitality, healthcare, and customer service, to satisfy these sectors’ unique translation requirements.
- The increasing internet usage in emerging nations creates chances for AI translation manufacturers to provide localized language solutions, allowing businesses to target and increase their reach in these markets.
- There is an increasing need for AI translation solutions that can be tailored to individual tastes and needs.
- Manufacturers may capitalize on this potential by creating versatile and adjustable translation systems.
- Despite major developments in AI translation systems, they may still have limited language capability when compared to human translators.
- This can be a barrier for manufacturers operating in specialized markets or targeting languages with limited resources for AI translation development.
- Manufacturers’ capacity to successfully communicate with their intended consumers may be hampered if particular languages are not supported.
- To get reliable results, AI translation models rely largely on massive volumes of high-quality training data.
- Obtaining such data for each language combination and domain, however, might be difficult.
- In certain circumstances, data may be sparse or insufficient, particularly for languages with fewer digital resources.
- This can have influence on the performance and reliability of AI translation systems, as well as the capacity of manufacturers to produce high-quality translations.
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AI Translation Market Segmentation:
Market Breakdown by Applications:
- Translation App
- Translation Machine
Market Breakdown by Types:
- Online Education
|The Market size value in 2023||USD 650.8 Million|
|Revenue Forecast by 2033||USD 3520.9 Million|
|Growth Rate||CAGR Of 5.7%|
|Regions Covered||North America, Europe, the Middle East and Africa, Latin America, and the rest of the world|
|Short-Term Projection Year||2028|
Along with researching the profiles of the top competitors in the AI Translation market, the competitive environment of the industry is thoroughly investigated. Some of the players profiled are Systran, DeepL, SDL, KantanMT (Ireland), Prompsit (Spain), Unbabel (Portugal), Pangeanic (Spain), Lucy Software, and Yandex. Translate (Russia), Iconic Translation Machines (Ireland)
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Key highlights of the report:
- AI Translation Market Performance (2018-2022)
- AI Translation Market Outlook (2023-2028)
- AI Translation Market Trends
- AI Translation Market Drivers and Success Factors
- SWOT Analysis
- Value Chain Analysis
- Detailed competitive landscape
Craig Francis (PR & Marketing Manager)
HTF Market Intelligence Consulting Private Limited
Phone: +1 434 322 0091
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