Machine translation

High school (ages 12+)
Science & Technology

Name:

Date:

Step 1 · Read the article

Open the article and read it at the level above. Then answer the questions below in your own words.

https://smallwhale.org/articles/machine-translation

Write what each word means, using the article.

Do not copy the article. Write two things you learned, the way you would explain them to a friend.

Answers below are taken from the article’s stored facts, so they match what the student read.

1. What is the category?Computational Linguistics / Artificial Intelligence
2. What is the primary applications?Global information access, cross-cultural communication, international business, localization, and scientific collaboration
3. How did machine translation start?It began with rule‑based systems that used big dictionaries and grammar rules, then moved to statistical methods that learned from many translated texts, and now uses neural networks that read whole sentences.
4. Why do machine translations sometimes make mistakes?Machines can miss jokes, feelings, or cultural details, so they sometimes give wrong or awkward words.

Parallel Corpus: A collection of texts that are translations of each other, used to train statistical translation models.
Transformer Architecture: A type of neural network that has become dominant in natural language processing, including machine translation.
Domain-Specific Customization: Training or fine-tuning MT models for particular subject areas to improve accuracy and relevance.