Learn Before
MT Evaluation
Translations are evaluated along two dimensions:
- adequacy: how well the translation captures the exact meaning of the source sentence.
- fluency: how fluent the translation is in the target language.
The most accurate evaluations use human raters. An alternative is to do ranking: give the raters a pair of candidate translations, and ask them which one they prefer. While humans produce the best evaluations of machine translation output, running a human evaluation can be time consuming and expensive. For this reason automatic metrics are often used.
0
1
Tags
Data Science
Related
Application of autoregressive generation given a prefix: Machine translation
Backtranslation
MT Evaluation
MT Corpora
Assessing Translation Effectiveness for a Specific Use Case
A company is developing a translation service for legal documents, where preserving the precise meaning and complex sentence structure of the original text is the highest priority. The company has access to a massive parallel corpus of legal texts. Given these requirements, which approach would be more suitable and why?
Evaluating Machine Translation Quality
Unaligned Data in Sequence Learning
Statistical Machine Translation (SMT)
Statistical Machine Translation vs Neural Machine Translation