[Updated for 2025!] 5 AI Translation Tools - A Comparison of Features!

1. What is an AI Translation Tool?

AI translation tools are tools that automatically translate languages using artificial intelligence (AI). They utilize technologies such as machine learning, natural language processing, neural networks, and deep learning to translate from one language to another. This facilitates communication and information sharing between different languages.

AI translation became widely known when Google announced the Google Neural Machine Translation (GNMT) in 2016 and began offering it to users. GNMT significantly improved accuracy over the traditional Google Translate service by utilizing deep learning.
Since then, deep learning has been adopted by other companies, leading to the emergence of more fluent automatic translation services like DeepL. In 2020, Google refreshed its neural network and introduced a technology called Transformer. As a result, both speed and accuracy have further improved.
This Transformer technology is used not only for translation but also in generative AI that has gained attention in recent years, such as OpenAI's ChatGPT, Google's Gemini, and Anthropic's Claude.

The basic features of AI translation tools include not only text translation but also file translation such as Word documents, glossaries, and translation memories. By utilizing these features, the translation process becomes more efficient and the accuracy of translations improves.

2. Differences from Generative AI Translation

This section explains generative AI translation and the differences from AI translation.

●What is Generative AI?
Generative AI is a technology where deep learning models trained on large amounts of data automatically generate new content such as text, images, and audio. Unlike traditional search or fixed output, it is characterized by its ability to infer context and create creative expressions from scratch. A representative example, ChatGPT, provides diverse outputs such as answering questions, translation, and summarization while interacting with humans. Its support use cases are expanding in companies for drafting advertising copy, in education for personalized instruction, and in research for hypothesis generation. On the other hand, issues such as misinformation, copyright infringement, and bias exist, so verification and the establishment of guidelines are essential when using it.

●Differences from AI Translation
Traditional AI translation (neural machine translation) generally refers to a bilingual corpus, calculates the probability of phrase correspondences, and selects the most likely words. On the other hand, generative AI translation generates the translated text from scratch by inferring characters and context from the trained data. A representative example, ChatGPT, can simultaneously follow instructions for various styles such as polite language, summarization, and explanations, and can interactively respond to questions about technical terms or unclear points. It also has the strength of inferring nuances and proposing expressions tailored to the reader. However, caution is necessary as it can be influenced by the training data and may produce hallucinations, outputting information that differs from facts.

For more details about generative AI, please see the article below.
"What Are the Risks of Generative AI? Explaining Necessary Measures for Its Use!"

3. Mechanisms and Three Types of AI Translation Methods and Their Differences

We will explain the mechanisms, three types of methods, and their differences in AI translation.

●RBMT (Rule-Based Machine Translation)
RBMT (Rule-Based Machine Translation) is a model that performs translation using dictionaries and grammar rules manually written based on human linguistic knowledge. It has been used since the early days of AI translation. It breaks down the input sentence and reconstructs the corresponding words and structures according to the rules of the target language, making it suitable for fields where technical terms and language structures are stable. On the other hand, it is weak against expressions not covered by the rules, such as colloquial language and new words, and a major challenge is the high cost of adding dictionaries and updating rules.

●SMT (Statistical Machine Translation)
SMT (Statistical Machine Translation) is a model that performs translation by statistically analyzing a large bilingual corpus and learning the correspondence probabilities between the source and target texts. First, the sentence is divided into words or phrases, and a "translation table" is created based on the frequency with which each pair appears simultaneously. Then, a "language model" that rearranges word order is combined to search for the translation with the highest probability. Compared to the traditional rule-based method, where grammar rules are manually designed, SMT has a higher adaptability to unknown expressions, but it has weaknesses in handling expressions not found in the corpus and in grasping long-distance context.

●NMT (Neural Machine Translation)
NMT (Neural Machine Translation) is an AI technology for translating sentences. Unlike the previously mainstream statistical methods, a deep neural network trained on vast amounts of parallel data processes an entire sentence at once while considering the context. As a result, its strength lies in generating smooth translations that naturally preserve word order and expressions.

For more details about machine translation, please see the following article.
"How Machine Translation Works: Literal Type, Free Translation Type, and Neural Translation Explained"

4. Advantages and Disadvantages of AI Translation

Explanation of the advantages and disadvantages of AI translation tools.

<Advantages of AI Translation>

●Cost Reduction and Time Savings through Translation Automation
By utilizing translation automation, it is possible to significantly reduce the costs and time associated with translation. Compared to manual translation work, leveraging translation software and AI allows for efficient document translation. Companies and organizations can perform multilingual translations in a short time while also keeping costs down.

●Improvement of Translation Accuracy
Another advantage of AI translation tools is the improvement in translation accuracy. Compared to traditional machine translation, the number of mistranslations has significantly decreased. Additionally, because AI translation tools learn from vast amounts of data, they can achieve high accuracy in translating specialized terminology and specific fields. Therefore, they are also suitable for translating professional documents and technical terms.

●Support for Multiple Languages
The AI translation tool's ability to support multiple languages is also a benefit. This allows companies to communicate smoothly with overseas branches and customers. It is a very convenient tool for companies aiming for global expansion, as it enables smooth transactions with different language regions. By utilizing the AI translation tool, efficient and accurate translations can be performed, which is expected to greatly contribute to business expansion.

<Disadvantages of AI Translation>

●May Lack Accuracy
There are situations where AI translation lacks accuracy. In sentences containing complex syntax or specialized terminology, the accuracy tends to decrease, leading to misinterpretation of context or selection of meanings that do not fit the context for polysemous words, resulting in mistranslations. In long sentences, some phrases may also be omitted from the translated text.
Additionally, translations of humor, sarcasm, or phrases with culturally nuanced meanings that differ from literal translations often result in unnatural translations.

●Human Review is Necessary
Relying solely on AI translation can result in publishing texts without noticing mistranslations, so human review is necessary. Especially for important documents, checking by professional translators is indispensable.

●Concerns about Security Risks
When using AI translation, it is also necessary to pay attention to data security. Especially when sending confidential documents such as legal or medical records, some services may save the content for learning purposes, and there is a risk that it may appear in third-party translation results through shared models. For these reasons, carefully check the terms of use and settings, and choose tools equipped with encryption and confidentiality functions.

For more details on the disadvantages of AI translation, please see the article below.
"What Are the Disadvantages of AI Translation (Machine Translation)? Explaining How to Overcome Them and Use It Efficiently!"