Automatic processing of sign languages can only recently potentially advance beyond the toy problem of fingerspelling recognition. In just the last few years, we have leaped forward in our understanding of sign language theory, effective computer vision practices, and large-scale availability of data. This project achieves better-than-human performance on sign language identification, and it releases a dataset and benchmark for future work on the topic. It is intended as a precursor to sign language machine translation.
As I haven’t yet created a permanent place to hold the dataset I collected for my most recent class project, I’m hanging it here for now. SLANG-3k is an uncurated corpus of 3000 clips of 15 seconds each of people signing in American Sign Language, British Sign Language, and German Sign Language, intended as a public benchmark dataset for sign language identification in the wild. Using 5 frames, I was able to achieve accuracies bounded around 0.66/0.67. More details can be found in the paper and poster created for CS 231N, Convolutional Neural Networks for Visual Recognition.
Many thanks to everyone who helped with this project — and most especially to the anonymous survey respondents who received only warm fuzzies as compensation for taking the time to help with this early-stage research.
One of my favorite parts of studying linguistics was being presented with data and being asked to find the system within it. Language data, with linguistic theory’s insistence that everything must make sense, make the most excellent data and logic puzzles.
As part of preparing for a spatial grammar-heavy meeting of the Montgomery Blair High School Linguistics Club, I developed three American Sign Language morphology problems. These problems illustrate interesting properties of American Sign Language that spoken languages do not have (non-manual markers, spatial agreement, and a rich temporal inflection system based in manual phonology).
Try your hand at doing the problems if you’re interested in any of the following:
What it means to do theoretical linguistics (or the sort of logic skills that linguists develop)
Unique properties of spatial languages
Basic American Sign Language linguistics
Similarities between American Sign Language and other world languages
Unlike most materials on ASL linguistics, the problems don’t assume that readers are fluent in American Sign Language or in linguistic theory — I developed these problems because I couldn’t find any resources aimed at an intelligent lay non-Deaf audience. The problems deliberately walk users through the steps to answer a question, whereas most theoretical linguistics problem sets jump straight to the questions at hand and assume existing familiarity with linguistic features not observed in English.
Once the club and I meet, I’ll post the answer sheet as well.
During the discussion we focused on introducing different non-voiced communication forms and on linguistic anthropology/linguistic creativity. We postponed theoretical linguistics until another time (in which we did some experiential learning on morphology). This page consists of a set of links, prepared videos, and notes designed to support real-time interaction with students at the linguistics club at Montgomery Blair High School.
The big take-away is that American Sign Language is not “English on the hands”. ASL is independent from English both in grammar and linguistic culture.
Introduction
Caveats for posterity: I’m hearing, I don’t possess native-like fluency in ASL, and I don’t have an advanced degree in this; I do have general and ASL linguistic training, I read widely, and I’m more or less aware of what I don’t know
What are some ways deaf people communicate? [YouTube]
Compare ASL structure [.avi | .ogv | .gif] with PSE structure [.avi | .ogv | .gif] with English structure [.txt]
YouTube has a variety of performances, lectures and vlogs
What’s this blog about?
Whatever is on my mind. The content has varied over the past more-than-decade, but it's always been technical. In the early years I focused on improving the fabric of the internet for some niche tools. But the internet no longer needs that kind of improving, and search doesn't really work like that anymore either. This blog is currently mostly about documenting notes for my future self, and sharing those notes with anyone who is interested.
