Tag Archives: Academic

Google Translate in a fourth-grade classroom

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I teach the fourth grade in a public elementary school in the suburbs of a large U.S. city, and in my classroom I often have a child or two with very limited English skills. These kids are 8 or 9 years old and often here with parents who are stationed temporarily in the U.S. They get daily or weekly time with the ESOL (English for Speakers of Other Languages) teacher, but other than that, they are fully integrated into normal American classrooms.

I use Google Translate with these children in a very focused, need-to-solve-a-problem basis. I have a specific question I need to ask, an instruction I need them to follow, or I need to get information from them. Things like, How are you going home today? Are you going to buy lunch in the cafeteria today or did you bring a lunch? You know, the kinds of daily activities in the life of a classroom.

When I was in the third grade my dad got posted in a foreign country for a year, so I actually know what it’s like for those kids. You’re just sitting there in a fog while everyone around you speaks Russian or some language you can’t grasp. Nowadays I have a tool I can use to help kids in a similar situation through the school day: Now we’re going to do this. This is what you need to do. Those kinds of things are important for their general feeling of well-being, that they can manage the school day.

Julia_GT excerptI sometimes use it in other ways. During writing lessons, I might have a child write in their native language. Then I copy/paste that into Google Translate so I have an idea of what they’ve written. I figure at this stage, writing in your own language is better than trying to write in English. I’ve even tried translating larger blocks of text for a student to read so they can at least know what is being discussed in class.

The languages I’ve dealt with so far are French and Spanish. I had Latin in high school so I can recognize word derivations and root words and can be somewhat assured that what’s been translated is moderately close to what we’re talking about.

When you’re communicating this way, you have to read between the lines a bit. It’s usually so situation-specific that you can get the meaning, but once in a while it takes some back-and-forth questions and answers to narrow things down and get an understanding. Luckily if we hit a dead end, I usually have a backup: a school employee or another child who speaks the student’s language. If that method fails, we can always call the parents to sort things out. At least one of them usually speaks English.

As the kids learn more English, I find myself using machine translation more. I can tell that they are starting to understand me a bit and I want to communicate more. I first say something then I type it into Google Translate. They can see the connection between what I’m saying, what I’m typing, and then what it goes out to in their own language.

I feel like machine translation is a resource that I can use to move to the next step. It really feels like a bridge for understanding.

Whatever else happens, I want these kids to feel like they are understood.

Helmuth, University Lecturer

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I use machine translation to communicate with a PhD student in another country about her academic work in our field of translation studies. She is researching a topic I know well and have written several articles on, and we have had a kind of e-mail collaboration going on for several months now.

The main language of our discussions is English, but there are several other languages involved. My command of English is more of a passive one, I am of course much better with my native German. Her English seems to be better than mine, though her research work is done in French and her native language is Chinese.

It usually works like this: She writes me mails in English. My English is good enough that I can read them directly. I want my replies to be well thought-out so that they are useful to her, so I write and edit them in German until I am satisfied. I then put the German text into Google Translate and translate it into English. I still edit the English a bit, most often to correct mistranslations of keywords from our specific field. When it’s all ready, I copy/paste the English into the mail.

I actually often include the original German text too. Sometimes I do that because I’m not 100% sure the English version came out saying what I wanted to say or if it will be clear enough. I figure that if I include the original, then she can compare the English with the German, or try machine-translating the original German into a language she knows better, like French or Chinese. Or she may even have access to a different MT tool that gives her better results.

Strictly speaking, we wouldn’t have to do this through machine translation because I do know some English. But it would take so long for me to produce English from scratch! I would sit for hours looking up individual words. I would definitely end up writing shorter and simpler messages, plus I would write less often. I’ve decided using machine translation is the fastest and best method.

Actually this is not the first time I’ve used this kind of solution. 10 years ago I had some collaboration with an academic in Spain and we used it then. We each visited the other’s university and we spoke English when we were together. But for all the communications needed to plan and organizing these visits, we used Babel Fish to translate between German and Spanish. That worked well. We once had a slight misunderstanding that came from the translation of one word, but it was soon cleared up because the context made it clear that it didn’t mean what he thought at first. It can happen that way sometimes – the context corrects things.

Of course the texts you translate in Google are not ready for any kind of publication. That is clear. But for this purpose, it is a valuable tool that saves me time and makes things easier.

Having said that, I’ll add that on the other hand, I find it interesting that people seem to want to believe that language is a system that can be mechanically produced. So much money – millions – has gone into researching these systems. Much more money than they’ve used for more sensible things. I guess it’s just the way people think; they don’t remember that words are only signs that represent mental concepts. The full meaning of words comes only through their relation to a specific situation and context.

Dr. C. Koby, Physicist*

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Oak Ridge National Laboratory, Tennessee, USA
October 15, 1971

Part of my work as a physicist is to keep abreast of research being carried out in my field. I try to follow activities in all parts of the world, but I am particularly interested in the research being conducted in the Soviet Union. I would guess that something like 15% of the articles and books I need to read in my field are written in Russian. I have no competence in Russian so have to rely on translations to access those materials.

A very positive development in the past few years is a service that my laboratory offers which machine translates articles from Russian to English. They don’t have anyone correct the articles,  you get what the machine puts out. I have personally used the service 10 or so times over the past 3½ years.

I have one simple reason for using the MT service: it is fast. After a request, I can expect to get a machine-translated article back in 1 month, much more quickly than the 9-10 weeks some colleagues report waiting for articles translated by humans.

More time and effort is required to understand machine-translated texts as compared to those written in English – I’d say about double the time. One reason for that is that formulas and diagrams from the original articles do not get translated, so I usually have both the machine-translated text and the original Russian article, and I go back and forth between them. In general, however, I’d say that the quality of the translations is acceptable. In a funny way, over time you get used to the style. You find yourself mentally correcting awkward passages.

I think it’s important to bring up the fact that the machine translation is understandable to myself and my colleagues mostly because we are familiar with the contexts being discussed. We know our own fields well and that allows us to accommodate texts that are not perfect. It is also important that technical terms are translated correctly or at least understandably, and the majority of the time, they are. The most common problem is words that are left untranslated. I don’t know why that happens but it does, and it can affect understanding.

I’ve been asked if it would be possible for someone to completely misunderstand the machine translations and arrive at the opposite meaning from the original. Yes, sometimes the meaning is a bit distorted, but since I know the context of what I’m reading so well, I do not think that it is possible to arrive at the opposite meaning. I have never heard of it happening anyway.

Overall, I’d say that I’m happy to use the service. It allows me to read things I would normally have to wait far longer to get access to. I would, and actually have been known to, recommend the use of machine translation to my colleagues.

*       Instead of being about 1 real person, the persona in this story is a composite that is based on a group of 58 real people who were surveyed by Bozena Henisz-Dostert in the early 1970s (see reference below). The group consisted of some of the first users of one of the first machine translation systems: the Georgetown Automated Translation system, developed in the 1950s and early 1960s at Georgetown University. Although its development was discontinued in 1964 due to lack of financial support, the Georgetown system continued to be used, virtually in its 1964 state, for a decade or so by 2 groups of scientists in Oak Ridge, Tennessee and Ispra, Italy.

The persona in the story was compiled in a straightforward way. I used 23 of the survey’s 51 questions. For each question, I took the most popular answer, or the mean or average of the figures given in answers, to describe Dr. Koby. The name ‘Koby’ came from an internet name generator and does not reflect any one true person.

The story is based entirely on information from Bozena Henisz-Dostert’s article ‘Users’ evaluation of machine translation’ in the book Machine Translation by Henisz-Dostert et al. 1979.

 

Mary, machine translation researcher

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Recently I’ve gotten interested in historical machine translation (bet you didn’t know that exists!) I found a fascinating study of some of the first users of machine translation. They were using the Russian-English system developed at Georgetown University in the 1960s. Most were scientists who lived and worked either in the U.S. or in Europe. The study was very comprehensive, conducted mostly through interviews with the people.

The book also mentions that a user study was done in the same time frame in Russia with users of one of the first systems there, which translated between French and Russian. There is a one-sentence mention that the study had similar results to the American one and that the researcher, Olga Kulagina, was at the time intending to write a book on the system and the user study.

That sends me on a wild goose chase for that user study. I pinpoint 1 book and 1 article by Kulagina in 1979-1982. I start with the book, ordering it through the library’s long-distance loan. Yesterday I get a note that it arrived. I excitedly go to get it and it’s not until I get back to my office that I remember a small but annoying fact.

I don’t know any Russian.

I send a note off to a student asking if they want to help me but I can’t stand to wait for her answer, I have to know right away if the user study is covered. Google Translate app to the rescue! I whip out my phone and start hovering…

book1book2

This app, as many of you know, is not at its finest in skimming books. I patiently move it through the table of contents, though, and get a fairly decent idea of what kinds of information is in it.

End result: dead end on the user study, looks like it’s not in this book. I’ll have to try the 1982 article. But it’s nice to get an answer so quickly.

And somehow I think that Olga might like the idea of someone reading her work on machine translation through a translation app in their phone.