গাইড লিঙ্ক ক্যুইজ · মাঝারি স্তর
মেশিন অনুবাদ কুইজ
অনুবাদ ডেটা সারিবদ্ধকরণ, টোকেনাইজেশন, BLEU সীমা, ভাষা-জোড়া মূল্যায়ন এবং শব্দার্থিক ত্রুটি যেমন পরিবর্তিত সংখ্যা বা নেতিবাচকতা পরীক্ষা করুন।
প্রশ্ন 1 এর 8
What does parallel training data contain?
প্রতিটি প্রশ্নের পূর্বরূপ দেখুন8 প্রশ্ন
আপনি কুইজ নেওয়ার সাথে সাথে উত্তর এবং ব্যাখ্যাগুলি উপস্থিত হয়।
- What does parallel training data contain?
- Source passages paired with corresponding translations
- Unrelated documents grouped by font
- Only target-language references
- A list of model predictions without sources
- What can mismatched source-target alignment teach a translation model?
- A guaranteed improvement in fluency
- The wrong relationship between passages
- A correct translation for every language
- A better BLEU reference
- Why keep related documents together when splitting evaluation data?
- To remove the need for references
- To make tokenization identical
- To reduce near-duplicate leakage across splits
- To increase sentence length
- A tokenizer splits one writing system into many more units. What should evaluators check?
- Whether source and target use the same alphabet
- Only the model’s name
- Whether BLEU is always high
- Length limits and whether either passage is truncated
- What does BLEU compare?
- Whether a translation is legally valid
- Patterns of word sequences with reference translations
- The full meaning and readability of a passage
- The number of languages in a model
- A candidate translation changes “did not arrive” to “did arrive.” What error should reviewers flag?
- An insertion that cannot matter
- A casing normalization choice
- Incorrect negation that reverses meaning
- A target-language tokenization win
- A model has a strong average score across several well-resourced languages. What could that conceal?
- Poor performance in a less-represented language or specialized domain
- That all language pairs are equally reliable
- That there are no terminology errors
- That the test set has no duplicates
- What should accompany an automatic metric in translation evaluation?
- A single score without settings
- Only a larger reference corpus
- An assumption that meaning is preserved
- A documented setup and bilingual review of specific errors