The theme of this year’s NAACL, which ended last week, was data bias and privacy, topics of great social consequence. On the former, many…
A very good overview by Adina Williams of why machine translation is hard and why it’s useful to have humans (and especially linguists) in the loop to know which things require more context. Excerpt:
So, now we’ve seen three new examples of where translations fail. They are very well controlled: in each example of a translation mismatch, we’re translating only a single sentence with only one grammatical system. In reality, pairs of languages may differ across numerous grammatical systems, even within the same sentence. We could have wanted to translate Turkish sentences with both “genderless” pronouns and evidentiality into English, and then we would multiple the potential translation alternatives.
These three examples are just the three I could think up off the top of my head post-NAACL (as I write this, I’m reminded of others to try: we could look at translation mismatches in case, determiners and definites, question particles, clusivity, numeral classifiers, and this list could definitely go on and on).
Read the whole thing.
