Read more: 5 Considerations When Measuring Machine Translation ROI
In selecting the machine translators below, we evaluated their performance in these languages: French, German, Spanish, Chinese, Japanese, and Korean. We chose these languages because they are widely used globally. Here is how the different machine translators perform with these languages:
Google Translate
Strengths: Google Translate is good for French, German, and Spanish. It provides quick and reasonably accurate translations and supports voice and image translation.
Example: Google Translate can quickly translate restaurant menus, providing a convenient and fairly accurate understanding of the available dishes.
Microsoft Translator
Strengths: Microsoft Translator is excellent for Asian languages like Chinese, Japanese, and Korean. It integrates well with Microsoft Office, providing real-time translations.
Example: Translating a technical manual from English to Chinese czech republic mobile database with Microsoft Translator ensures accurate use of technical terms.
DeepL
Strengths: DeepL excels with European languages, particularly German, French, and Spanish. It produces very accurate translations by understanding the nuances of these languages.
Example: Translating a German legal document with DeepL ensures precision and correct use of legal terms.
Best Practices for Using Machine Translation Engines
In researching for this article, we interviewed some of our project managers. Here are their tips and advice for using these engines efficiently and effectively.
1. Clear Input Text
For the best results, start with a clear and error-free text. Proofread the text to remove any spelling, grammar, or punctuation mistakes. Avoid using slang, idioms, or ambiguous language. Use simple and straightforward sentences to improve translation accuracy. Machine translation engines work best with clear and concise input.