Creating a Computational Linguistics College Degree?

$random_var asks: "I am an undergraduate student currently studying Bioengineering. However, I am growing more and more interested in programming and linguistics, which leads me to think that I should define my own major, Computational Linguistics [mit.edu], which google defines as 'a field concerned with the processing of natural language by computers.' When I present my proposal for this degree to the school's advising staff, I would like to have a complete list of all of the topics this major should cover. Having only little experience with computer science and engineering, I'm not sure what parts of that field I should include. Beyond the basic lower-division courses, what specific fields of computer science do you think should be emphasized in a practical undergraduate study of Computational Linguistics?"

Comments

As someone who has done some work in the field...

[Faizdog]

Computational Linguistics, or Natural Language Processing (NLP) as it was called for me, is one of the many areas that traditional Computer Science is exploring, in addition to things like biology (bioinformatics), etc.

I'd say the first two years in the major need to be very similar to the first two years in the Computer Science curriculum and last two in the humanities/linguistic area. The reason I say this is because a lot of the math, basic computer science, etc that is needed in the field will be the same as the core Comp Sci/engineering classes. However, the first two years in the humanities are very generic, and you specialize a lot later. So build up the core of Comp Sci and linguistical study early.

Then, get deeper. A lot of the NLP work is being done in Maching Learning/Data Mining classes. Make sure you take those, we had a whole class called Textual Data Mining at my university. Take algorithm design and some of the common advanced Comp Sci classes too, since a lot of the techniques are very advanced, being developed, cutting edge and will require research. Take advanced statistics classes too, much of the field is built on statistics.

NLP is a very interesting area, but I don't know if it deserves its own major yet. I would advise majoring in comp sci, with a concentration in Machine Learning/Data Mining through your technical electives. And a minor, or perhaps second major in Linguistics. I'd say minor because then you could take only the classes relevant to the field, instead of all the other stuff related to a humanities major that you may not want.

Anyway, that's my take. I did a bunch of NLP research, even getting work published as an undergrad, and I was a Computer Engineering major. The field is as such that it's so new and emerging that not much formal linguistics study is required right now, if you are a native english speaker you are probably good. But, it doesn't hurt to get a more formal background in it, that's why I suggested the minor.

A.I.

[cmarks03]

The only thing as a CSE student that pops out at me is Artificial Intelligence-related courses. Though if you ask me, the best way learn how to do something is by doing it (assuming you have taken the entry-level courses like C, etc). I'm doing an internship (co-op) right now that will help me in at least three classes I have to take still.
Also, just thinking and re-reading, some language classes would be handy. Though the elementary school english about nouns/verbs/etc will help, you'll need more if it's to process natural language.
Another thing is some data structures classes. One project in one of my data structures classes dealt with the computer making up a sentance based on a template (the "grammar") and the stuff to plug into the template (the dictionary). You're looking at the exact opposite but with a difficult to define "grammar" and a huge dictionary.
Plus anything that would help you in implimentation in software such as database usage, etc.

Don't do it

[AuMatar]

Not as an undergrad. You're still learning, still ought to be figurin g out what you want to do. Get a good, well rounded CS education. Maybe take a few courses in linguistics if the subject interests you. Then specialize in computational linguistics in grad school if you decide its really what you want to do.

Basicly, undergrad is to learn the field. A masters is to specialize in one domain. A doctorate is to research a single problem in as much depth as possible. They're in that order for good reason- it leaves you plenty of room to change your mind and interest as you grow older, while keeping you marketable in both industry and academia. Don't specialize too early, or you may regret it later.

Re:Don't do it

[octavist]

I concur. In fact, I did what you are trying to do, complete with Engineering Open House project that conversed, and stored info in a semantic network. Then I had wonderful interviews with various NLP heavyweights (of the era). When one gentleman said, "I'm going to do everything I can to see you get an offer", I realize in retrospect that he meant, "...since you only have a Bachelor's Degree." CS, lots of graph theory and algorithms. Take a few linguistics courses on the side. What he said. Then do this in grad school.

Is a separate major really necessary?

[dslauson]

To me, this sounds like a good idea for your specialization for a masters degree (in computer science), but I don't really think it justifies it's own undergraduate degree. If that's what you're really interested in, I recommend majoring in CS as an undergrad, perhaps with a minor in english, and then submitting this your linguistics stuff as your masters thesis when you get there.

Of course, there are a lot of classes to steer you in that direction. From the computer science field, you have to take compiler structure. That may not sound like a relevant class, but it is. Learning to write good lexers and parsers is going to be vital, and that is the class where you will learn them. Also, seeing how a high-level programming language is parsed can give you a lot of insight into how natural language will be parsed.

Of course, an AI class would be helpful, too. And machine learning, but that's not always offered at the undergraduate level.

Outside CS, I would also recommend taking at least one foreign language to give you a little more basis in how syntax and grammar vary across languages. A non-latin based language, like Japanese, might help.

Re:Is a separate major really necessary?

[Dr. Spork]

I agree with the parent. If I were a potential future employer or if I sat on an admissions committe for grad school, I'd look at your "custom degree" and say this to myself:

"Here's a kid who wanted to get out of having to take the hard CS classes, so he made up a major that sounds sexy and then slacked off. He just couldn't hack the real CS program."

Now, I'm not saying that this is you. If this would be a mistaken perception of what you're doing, I advise you to not invite the mistake, prove to everyone you can satisfy the requirements of the CS degree, and that you're motivated to do this extra work on linguistics. Then you'll look good. And, you'll have a non-hokey degree that might help you get a job even if you one day decide to not do language processing.

is this really appropriate for an undergrad degree

[blackcoot]

i don't believe that your chosen major is sufficiently broad to be useful. i also believe that, unless you intend to immediately pursue a graduate degree, you're likely to find it very hard to explain to potential employers what, exactly, it is that your degree says you can do. i don't know that anyone can develop the degree of maturity in the fairly wide set of disciplines that you'll have to master (general comp. sci., intro a.i., "soft" a.i., statistics, linguistics, and quite possibly some signal processing) to really succeed at this major as an undergrad. i suggest instead that you do a major in comp. sci. (or e.e., or linguistics) with a concentration in computational linguistics and then pursue further study at the graduate level.

Markov Chaining

[conJunk]

Markov Chaining, as applied to language, is really interesting.

It involves taking a canon of text (for example, the complete works of shakespeare, or every example of written english you can get your hands on, or every example of transcripts of spoken english you can get your hands on) and subjecting them to a statistical analysis of what chucks (that is, words, phrases, what have you) are likely to follow which other chunks.

while the outputs tend to make little sense, it is "interesting" to see what kinds of "statistically probably" examples of language a computer can make based on the training (input) you've given it

You May be a Cunning Linguist

[Anonymous Coward]

But I am a Master Debator

Start talking to professors

[HalWasRight]

When I present my proposal for this degree to the school's advising staff, I would like to have a complete list of all of the topics this major should cover.

Something to keep in mind whenever you want to have a group of people approve of something is to already know that they will. Start talking to the advising staff. In particular start talking to professors. They would need to approve, and for a custom major you'll likely need an adviser. Who on the faculty do you think would be appropriate? Approach them. If the first one is a pompous ass (as some academicians are), then find another. And another. A good prof will recognize you as a potential grad student, and therefore a potential resource to be exploited as is their job (I'm only half joking), and therefore a resource to be developed.

Maybe you don't need a new major, just some undergraduate independent study. My first research publication started as a special project after a class (it was a cogsci paper). It showed up in print at my school's library the day I completed my last undergrad final in compsci. By that time I was already enrolled in grad school where you really do make your own personal major. Either way it is the same process.

Re:As someone who has done some work in the field.

[negative3]

NLP is a very interesting area, but I don't know if it deserves its own major yet. I would advise majoring in comp sci, with a concentration in Machine Learning/Data Mining through your technical electives.

That's the first thing I thought when reading this question. This seems way too concentrated for a bachelor's degree. I'd say either doing computer science or computer engineering would be the way to go, followed by grad school. Find the right school with the right research group and/or professor and make that your thesis research. I'm not too familiar with the topic of NLP, but if there aren't any good books written on the topic go for your PhD and turn your dissertation into a book on the subject (a couple people from my graduate research group did that).

My main advice though is this: don't get too specialized for your BS. If you have lofty goals for research (as I'm assuming you do), go to grad school (as I said above). If you don't have much experience with programming or engineering, make your major CS or computer engineering. With computer engineering you'll get the programming background along with a solid understanding of engineering principles, and you'll more than likely be able to take advanced CS classes like AI or something. Oh, and some sort of linguisitcs would seem (to me) to be necessary, as the parent stated (somewhat).

notes: I admit that the parent obviously know way more than me on this subject. I'm just adding my own $0.02. I'm biased towards the engineering (I do have an MS in EE). The best programmers I've ever met were not CS students, they were physicists and engineers (I'm not a great programmer, I barely know C++).

Don't Make Your Own

[coaxial]

Make-a-Degree programs are for underwater basket weaving. Computational linguistics is an advanced topic. You won't touch it, nor should you, until a graduate program. You don't know enough about computer science to do anything advanced yet. Get yourself a CS degree and take some linguistic, anthropology, and psychology electives, then apply to a graduate program and do CL as your thesis. Read some CL papers and apply to the schools that publish in the CL journals. University of Washington has a program in CL consider applying there, or at least read their prereqs.