simultrans-demo.github.io
Curious how this would work translating between a language like German where verbs sometimes are placed at the very end. Or even if clauses make things complicated. You wouldn't know the meaning for a long time -- or would you guess and amend?
To make this concrete (DE <-> ZH) with EN provided for clarity, apologies for errors:
[EN] I didn't go out last evening, because my mother had warned me about feral cats on the street.
[FROM ZH] 昨晚我不去出因为我妈妈警告我街上有野猫。
[TO DE] Gestern Abend bin ich nicht rausgegangen, weil meine Mutter mich vor Wildkatzen auf der Straße gewarnt hatte.
In that German sentence, the key verb in the second clause "to warn [warnen]" happens nearly at the end, but in the beginning in Chinese [警告].
So if I'm halfway through the second clause of my Chinese sentence, ...因为我妈妈警告我, the simultaneous translation in German is "weil meine Mutter [.....]" and then all at once "mich vor Wildkatzen auf der Straße gewarnt hatte" when the Chinese sentence finally ends.
I suppose you could split the clause again to give some "early" meaning in the sentence in real-time: "weil meine Mutter mich davor gewarnt hatte, dass [...]" and then the bit about the wild cats when it shows up in the Chinese sentence, but I'm sure you can construct more pathological examples so my question still stands.
:)
same thing you do when you listen and try to guess where the conversation is headed. ;)
also with the same flaws when you guess wrong.
The example you gave is idiomatic Chinese:
> 昨晚我不去出 , 因为 我妈妈警告我街上有野猫 。
However, this is also idiomatic Chinese:
> 我妈妈警告我街上有野猫 , 所以 昨晚我不去出。
The order of two parts can be interchangeable depending on what you want to emphasize.
So I think any AI that is complex enough can handle this difference in ordering quite easily.
Also, if you see the gif before Demo I, it implies that the word "meet" is inferred before it actually appeared, which is exactly what you described.
I think in such a translation system (to text) you could just insert a placeholder and replace it later. Or (in speech) you'd just delay the sentence until it is complete. If you reach a timeout, you just render it ungramatically in the wrong word order. Especially when speaking freely and making up the sentence on the spot, you could say something like "because my mother... about wild cats on the street... [uhhm, you know] ... she warned me".
Chinese also sometimes has "strange" word order for western ears, when you just state the "topic" upfront instead of building a relative clause like you would in English or German. "[Talking about] wild cats on the street, my mother warns me".
A live translation system will always have a tradeoff between accurracy+elegance and latency, just like real human translators.
–
Word-by-Word Translation: river zemin correct united states president of speak express regret
Simultaneous Translation (wait 3): jiang zemin expressed his welcome to the us president 's remarks .
Simultaneous Translation (wait 5): jiang zemin expressed his regret over the us president 's remarks .
Baseline Translation (greedy): jiang zemin expressed regret over the us president 's remarks .
–
The "wait 3" model and "wait 5" model have a fixed 3 and 5 words, respectively, of "buffer" before they have to start translating. In this case, the Chinese word corresponding to "regret" comes between 3 and 5 words after its corresponding position in the English sentence. "Wait 5" is able to see it, but "wait 3" simply has to guess what goes in that position – and what it guesses is almost the exact opposite of the actual meaning! And it doesn't seem to be able to revise its translation after the fact.
To be useful in practice, you would definitely need to be able to do that. It seems like it would also help to dynamically vary the buffer size based on the amount of ambiguity – but according to the paper on arxiv, previous systems already did that, while theirs intentionally throws it away in favor of a fixed buffer, apparently because it's simpler to train and because they prioritize low latency.
Anyway, great story, I'm sure, but it seem apropos.
The propaganda push in Western media to build up and legitimize Chinese academia and technology ventures is staggering. Check out that map at the bottom. This article is more popular in EU and US than China itself. 99.9% of the chinese economy is built around stolen or borrowed technology. So what would be a minor development by a western researcher is a "breakthrough" for Baidu.
>Don't be snarky. Comments should get more civil and substantive, not less, as a topic gets more divisive.
>Please don't post shallow dismissals, especially of other people's work. A good critical comment teaches us something.
These are great guidelines, I really appreciate the thoughtfulness of whoever wrote them.
I don't know enough about languages to be able to tell if some advance is a major breakthrough or not, but people on Hacker News share and applaud minor improvements in many personal or professional projects, so I don't see why a Chinese project should be held to a different standard on this forum in that regard.