Open Source software makes a difference

In this video series on linguists in the field collecting data and providing language revival materials we can see that they are using Audacity to record their informants :) Koodos to the Audacity developers and contributors!



One might observe that it announces a potential future rise in Sierra Lione nationalism if not accompanied by encouraging the kids to think about iLanguage and Sociolinguistics. Child's choice of Hebrew as an example of a successful revived language is a very interesting one...

Mystery Language Quiz from Omniglot

The Omniglot has an interesting mystery language post this week. The data comes from http://globalrecordings.net/en/program/C08780.

A classic intro to Linguistics: Ali G interviews Chomsky

I still love this video, 3 minutes and digestably informative. In Quebec "linguistique" seems to mean that you've memorized

• lots of long proper words, and
• odd conjunctions and
• opaque grammar that no one uses

It's very very hard to explain what linguistics is, and why it could be useful to view language in that way...let's let the dynamic duo of Ali G and Chomsky explain it to us!

My Gtablet goes Gingerbread!

Thanks to installing the sample speech recognition service in the android sdk on my gTablet (which was running a hacked version of Android because the software Viewsonic provides only allows English keyboards and no Market!) I started getting Android.process.acore errors so I decided it was time for an upgrade, if not to honeycomb why not to Gingerbread?

I followed this tutorial, and was up and running in less than ten minutes!

Gingerbread is so much fun, or at least the vegan tab version is. It has a thumb keyboard that I'm using to write this. I don't know if I'll keep using it but its fun for now ;) I had been planning on skipping from 2.2 to 3.0 but I'm glad I had the opportunity to try it...

Posted using my Android

What kind of linguist did they say they were?

In Montreal Linguist means "linguiste" i.e. a translator. It turns out there are others who specialize in human language.



Someone on the ling department mailing list sent this around from Foxtrot. The classic reaction from most linguists is the first below, I added some other from other linguists I've met in the field for fun :)

Ling 101 teacher :

This comic merely promotes polyglot-ism. Many very influential linguists didn't need to speak any language other than English.

Field Linguist:

Hmm, let's see the first three are clearly French, Spanish, Italian.Hmmm, the fourth based on vowel diphthong and no orthographic h might be Portuguese, the fifth is clearly different. It must be an isolated cousin like Romanian.

• /a/ <-> /ju/,


• /m/ <-> /b/,


• /o/ <-> /i/ /____r.


• The final vowels might just be a suffix.

It's possible that the guy making the comic fudged the data to make "a hard one" so laypersons feel some achievement. Those post verbal pronouns look fishy compared to other Romance languages. Wonder if Romanians usually say "Love of mine" or is this a fail on the part of the cartoon author's use of Google translate...

• Quick chat with Romanian informant (if no informant, log into an online dating website with a Romanian profile and wait for fish to bite) reveals that hunch is on the right track, the guy did change it from salut to /buna ziwa/ probably because salut is also French.

The sixth looks like a mixture of Spanish and Portuguese, it's a toss up, maybe some reverse engineering on Google translate will tell me. I bet they started with Spanish, yep it's Catalan...

10 minutes later, all languages are identified, Google Translate is discovered and new correspondence rules for Romanian <-> Spanish added to mental storage (Spanish previously chosen as generic Romance language due to being field linguist's first Romance language and no obvious need to switch to another to date).

Computational Linguist:

Ah cool! I can send this to my computer sci/SOEN buds and they will think I'm pretty cool to be a linguist :) I'll hack together a Python script that uses the Google Translate API on my Android/Ubuntu machine and generate a few other languages to stump them even more. 3 minutes later all language identified, 3 hours later a new API learned.

Text Engineer:

Fun data! I'll run OCR on the gif on the command line, ripe out the text, send it through my language identification pipeline. 3 min later, all languages are identified (Catalan miss-identified as Spanish) and off to a bar for happy hour.

Soon all linguists will be first generation

At a Machine Learning talk last year the speaker was presenting his neural net which, if given Wikipedia data could learn to tag parts of speech, disambiguate words and even give pretty OK parse trees for any language. My thought (as a linguist who deals with lots of data in many languages) was "Cool! Bet it's not great, but at least its less bootstrapping that I have to do when I start navigating a new language's data." But the speaker said in question period that "linguists" disapprove of his approach, generally with some concerns that we cannot determine what his model is doing. Yeah, thats certainly true, since the nodes don't correspond to human knowledge explicit knowledge models. But I don't need the computer to model the data, I just want some rough clusters and classification so that I can go through the data and do the fine grained analysis using my human brain. We should also be careful with our human brains, we often over-generalize, see patterns that we think account for the data, but once we test them we discover that they account for only 10% of the data. To really account for the data we need a balanced approach, both large scale statistics, and some theoretical modeling...

When the speaker asked for a sample English sentence to test his model, someone offered "The cat the dog bit run" in an (incorrect) attempt to offer a center embedding example. As the audience member tried to reformulate his answer I realized this was the "linguist" that Machine Learning folks had met. Someone who had memorized sentences that Linguists find cool, in order to seem like a linguist at intelectual debates. I would also note, the other sentence the guy offered after failing the center embedding example was: "Colorless green ideas sleep furiously." Natural Language does have really interesting data, they should just go on the web and grab a sentence. Very few sentences are SVO, even fewer use center embedding or garden path like "The horse ran past the barn fell." Most sentences are chalenging for a model designed to recognize. There's no need to test the hypothetical sentences that were a challenge for our Transformational Grammar framework back when the textbooks were written.

That's when I realized that maybe that old quote about "hire a linguist and productivity drops" might be due to hiring "linguists" either back when most departments didn't emphasize comparative linguistics (pre 2000), or hiring a computational linguist who was raised by a linguist who was raised by a linguist back in the days of Transformational grammar when comparative linguistics either didn't exist or meant working on Native American languages and inventing "adhoc" grammatical categories because Latin grammar wasn't good enough to account for the data. It's not that linguists are useless, it's just that like every other field you need one with real experience and training, not just someone who did their homework and read their textbook. Generally you'll only get true experience during your PhD, but that is changing. More and more departments are putting fieldwork on their course offerings and teaching modern linguistics in their Intro classes, rather than a history of linguistics before they get to the modern part in the 400 level courses or worse, only once they are in grad school.

As a rough generalization, any "linguist" raised in a computer science department, or in many undergrad linguistics departments is better described as a 3rd or 2nd generation linguist. They are memorizing generalizations and simplifications that the profs of their profs taught them in the 1960s or 1980s! Linguist who do fieldwork or do comparative linguistics on the other hand have first hand access to data and don't just apply the generalizations they learn in school, instead they apply fundamental principles of linguistics to discover new patterns and generalizations. The more Natural Language Data we work on, the more useful principles we discover, if we let ourselves be human and not logicians. In my computer science courses I discovered that there was this similar tug of war between Computer Scientists who wanted to formalize everything in terms of logic, and others who wanted to make it work. Not all software can be written as formal algebras, not all linguistic generalizations can be either, especially if you dont know what are the primitive operations or the variables that the algebra operates over. Creating a chess game playing program is a challenge, but its the first step in artificial intelligence. Most games aren't played like chess, just like most sentences aren't SVO.

Since that Machine Learning talk I stopped introducing myself as a linguist, but rather as a fieldlinguist. At least then I can discover what the other person thinks a "linguist" is. There are lot's of linguists out there. As budding linguists in Ling 101 we learn to clarify that we aren't "translators," nor "polyglots" nor "philologists." I could also use comparitive linguist, or descriptive linguist, but that might be too close to something they think they understand. Field linguist is also technically true; I am a fieldlinguist. I use theoretical linguistics to inform my work, but its not the be-all and end-all of my research. Theoretical linguistics is still very young, we don't have good enough tools for Pragmatics, Discourse Analysis, Prosody or even Morphosyntax. I've spent the past 10 years in the field doing classic fieldlinguist things like immersing myself in Natural Language Data in context, hours of recording and transcribing and working with informants for a variety of language types and language families (Urdu, Korean, Romanian, Czech, Turkish, Inuktitut) etc..

Times are changing, many of my friends are doing a unit on fieldwork in their Ling 101 or Language and Society classes. It's fun for the students to "discover" that they can figure out a new language. They realize that they are human, and learning languages is what humans do naturally when exposed to data.

The Fresh Meat Principle

Recently I convinced one of my friends to go Salsa dancing on the beginners night, alone. I was operating on five years of observations which I would formalize below as the "Fresh Meat Principle."

The Fresh Meat Principle

Given any x such that

• x is female,


• x measures between 5'0'' and 5'4'',


• x is of medium to athletic build, and


• x is wearing flat practical non-salsa shoes

There will be a y such that

• y is male,


• y is aged between 25 and 45,


• y is a reformed geek, and




• either y is mid intermediate to mid advanced or


• y is interested in becoming a salsa instructor

In any w such that

• w is a beginner salsa night or


• w is an intermediate salsa night

Then y will monopolize x the entire evening in w.

I'm very happy to say the Fresh Meat Principle was upheld in a recent study.