Pretty neat, will have to try it out for Kiva. We translate a giant volume of words every year (we've translated nearly 100 million words total).
As it stands, we have an awesome community of volunteer translators who take care of most our needs, but sometimes in times of high demand we could use help getting through a large batch of loans to translate. That said, when we tested out some external services for leveraging machine translation and translation memories, what we found were a few problems that keep us from being able to leverage external solutions
1) Our volunteers don't like "post-editing", meaning what you are doing here of a human manually fixing up a machine translation. Since you are paying your translators, I imagine they don't mind though.
2) It seems the majority of companies are focused on English -> Foreign Language, whereas the vast majority of our translation needs are Foreign Language -> English, and this proved decisive with most of the software being geared in such a way.
3) Our partners are often in remote areas with not always the highest level of education, and often are writing in a language that is their second language (say perhaps French in a Senegal where the person's native language is Wolof), so the grammar of the French is not going to be great to begin with. This throws off the machine translation and makes it nearly impossible to develop a translation memory that is segmented in the right way to actually produce usable translation suggestions.
4) We need to review the text for policy guidelines (say for instance a partner puts in directions to a business by accident in a region where our borrowers are anonymized for safety reasons). But if we send a translation out to a service like yours and then just have the English back, and then need to report an issue in it back to the partner, the reviewer who would just know English would not be able to communicate back to the partner the issue and identify it in the original language version.
Anyways, just some food for thought in what we've had trouble with in the space of trying to help us get our lenders connected to our borrowers by providing them accurate translations of the borrowers' stories.
Thank you for your comment, very insightful concerns and advice. We would love to chat with you about your experience with crowd translation, it would be really helpful. Would it be possible to get in touch?
One thing that we could be useful for is to actually help your reviewers to communicate with the partner, that is to help in translating the communication itself.
In any case, Kiva is an amazing organization, so obviously we would love to find out how we can help in any way.
As it stands, we have an awesome community of volunteer translators who take care of most our needs, but sometimes in times of high demand we could use help getting through a large batch of loans to translate. That said, when we tested out some external services for leveraging machine translation and translation memories, what we found were a few problems that keep us from being able to leverage external solutions
1) Our volunteers don't like "post-editing", meaning what you are doing here of a human manually fixing up a machine translation. Since you are paying your translators, I imagine they don't mind though.
2) It seems the majority of companies are focused on English -> Foreign Language, whereas the vast majority of our translation needs are Foreign Language -> English, and this proved decisive with most of the software being geared in such a way.
3) Our partners are often in remote areas with not always the highest level of education, and often are writing in a language that is their second language (say perhaps French in a Senegal where the person's native language is Wolof), so the grammar of the French is not going to be great to begin with. This throws off the machine translation and makes it nearly impossible to develop a translation memory that is segmented in the right way to actually produce usable translation suggestions.
4) We need to review the text for policy guidelines (say for instance a partner puts in directions to a business by accident in a region where our borrowers are anonymized for safety reasons). But if we send a translation out to a service like yours and then just have the English back, and then need to report an issue in it back to the partner, the reviewer who would just know English would not be able to communicate back to the partner the issue and identify it in the original language version.
Anyways, just some food for thought in what we've had trouble with in the space of trying to help us get our lenders connected to our borrowers by providing them accurate translations of the borrowers' stories.