Becoming a computational linguist without double-majoring in linguistics and computer science

You’re an undergraduate, and you want to become a computational linguist? Here’s how to do it.

People who want to become computational linguists usually get a PhD in the subject.  Every once in a while, though, you run into someone who wants to study computational linguistics as an undergraduate.  In the United States, that means a student in what we call “college” and the rest of you call “university” (or, if you’re French, la fac’).  Undergraduate students in the US have one, and sometimes two, “majors”–the topic in which they will do the most coursework, and whose name will appear on their official paperwork when they graduate.  To “double-major” is to have two majors, rather than the usual one.  It’s not super-unusual to do this–I had a double major, in English and linguistics–but, it’s helpful to do a double major only if really necessary, as it’s a hell of a lot of work. 

If you’re getting a bachelor’s degree and want to be a computational linguist, a double major in computer science and linguistics is probably overkill.  (Overkill discussed in the English notes below.)  The most efficient way to become a computational linguist would be to get a degree in linguistics in a department that has computational linguists on the faculty, such as the University of Colorado at Boulder, or Ohio State University. If you want to try to become a computational linguist in a university that doesn’t have computational linguists in any department: first of all, your major should probably be linguistics, not computer science—computational linguists are a kind of linguist, right? (They are—I’m a computational linguist, and I’m a linguist.) You’ll want to do some coursework in the computer science department, but I wouldn’t actually recommend even a minor in computer science—that will probably require you to take some courses that won’t be the most useful ones for you, while taking up time that you could have been using to take courses that would be useful for you.

What should those courses be?  As many as possible from this list:

  • Corpus linguistics (usually offered in the linguistics department, but if your university doesn’t have such a course in the linguistics department, look for courses in the social science, communications, or media departments, possibly with names like “content analysis”)
  • Statistics (best in a linguistics or speech & hearing department–the traditional psychology department or agriculture school courses will kill you)
  • Machine learning (usually offered in a computer science department)
  • Natural language processing (presumably not what you meant by “computational linguistics,” or you would have said so)
  • Automatic speech recognition, if and only if you seriously think that you want to work in this area (often offered in the electrical engineering department)
  • Speech synthesis, if and only if you seriously think that you want to work in this area (again, often offered in the electrical engineering department)

Notice what’s not on this list: programming courses.  Take those if you know that you need them, but if you don’t know that you need them, then don’t take them.  Notice that I also haven’t said anything about linguistics courses: we’re assuming here that linguistics is your major, and you’re going to get a solid and well-rounded background in that field.

Picture source: Mariana Romanyshyn, Grammarly, Inc. https://www.slideshare.net/MarianaRomanyshyn/nlp-a-peek-into-a-day-of-a-computational-linguist-71510838


English notes:

overkill: doing way too much.  Examples:

How I used it in the post: If you’re getting a bachelor’s degree and want to be a computational linguist, a double major in computer science and linguistics is probably overkill. 

 

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