Automatic, or machine, translation tools fall into 2 categories – rule-based and AI-based.
Both translation tools have their own advantages and limitations.
Rule-based translation tools are based on a set of predefined rules and grammar patterns. They work by identifying the structure and meaning of a sentence and then applying the appropriate rules to generate a translation. They are generally considered to be more accurate for simple and structured text, such as technical documents and manual instructions.
AI-based translation tools, on the other hand, use machine learning algorithms to generate translations. They are trained on large amounts of data and can learn to understand the meaning and context of text. They are considered to be more accurate for more complex and unstructured text, such as literature and conversational language.
One of the main advantages of AI-based translation tools is that they can handle a wide range of languages and are not limited by a fixed set of rules. They can also generate more natural-sounding translations and are better at handling idiomatic expressions and cultural nuances.
However, AI-based translation tools can also be less accurate than rule-based tools, particularly for specialized or technical text. They can also be more expensive and require more computational resources.
In general, it depends on the use case and the type of text that needs to be translated. For simple and structured text, a rule-based translation tool might be more appropriate, while for more complex and unstructured text, an AI-based tool might be more suitable.
It’s worth noting that most of the professional translation tools use a combination of both rule-based and AI-based approaches to provide the best results. As technology is advancing, the gap between these two approaches is getting narrower and the AI-based approaches are getting more accurate and efficient.
Here is a list of some of the most popular machine translation tools currently available, and the category that each tool generally uses:
Rule-based translation tools
- Google Translate: One of the most widely-used machine translation tools, Google Translate supports over 100 languages and can translate text, speech, images, and even websites.
- Microsoft Translator: This tool is provided by Microsoft, supports over 60 languages, and can be used to translate text, speech, and even live conversations.
- IBM Language Translator: This tool uses machine learning to support multiple languages, it also provides integration with IBM Watson Assistant for chatbot and virtual agent use cases.
AI-based translation tools
- Amazon Translate: This tool is provided by Amazon, it’s a neural machine translation service that can be used to translate text in real-time, it supports multiple languages.
- DeepL Translator: This tool uses AI-based neural networks to produce translations that are often considered more accurate than those produced by other machine translation tools.
This list is not exhaustive and there are many other machine translation tools available on the market. Additionally, the features, capabilities and performance of these tools are subject to change.