Whoooaaa!

Looks like what we were doing RIGHT with our ASL vlogs since 2006! For a long time I was wondering if these vlogs have a significant impact in our community. I believe that there is an impact, for example:

• We became more active, mobilized and able to get things done to improve our lives.
• We also became closer as an ASL/Deaf community, since our community is so scattered all over the United States and sometimes in the world.
• We also become more and more fluent in American Sign Language and English.   The standardization of using our ASL signs are becoming obvious. For example, our sign of “language” becomes widespread by using two “F” handshapes, instead of using two “L” handshapes.

Lately, it is becoming a HUGE impact to the academic community too! Three researchers from Princeton University studied ASL vlogs on YouTube, DeafRead and Deafvideo.TV and they came up with an exciting conclusion about American Sign Language!

See abstract submitted in December 9, 2009 for Computer Science

Frequency of Occurrence and Information Entropy of American Sign Language
Authors: Andrew Chong, Lalitha Sankar, H. Vincent Poor (Princeton University)

American Sign Language (ASL) uses a series of hand based gestures as a replacement for words to allow the deaf to communicate. Previous work has shown that although it takes longer to make signs than to say the equivalent words, on average sentences can be completed in about the same time. This leaves unresolved, however, precisely why that should be the case. This paper reports a determination of the empirical entropy and redundancy in the set of handshapes of ASL. In this context, the entropy refers to the average information content in a unit of data. It is found that the handshapes, as fundamental units of ASL, are less redundant than phonemes, the equivalent fundamental units of spoken English, and that their entropy is much closer to the maximum possible information content. This explains why the slower signs can produce sentences in the same time as speaking; the low redundancy compensates for the slow rate of sign production. In addition to this precise quantification, this work is also novel in its approach towards quantifying an aspect of the ASL alphabet. Unlike spoken and written languages, frequency analysis of ASL is difficult due to the fact that every sign is composed of phonemes that are created through a combination of manual and a relatively large and imprecise set of bodily features. Focusing on handshapes as the ubiquitous and universal feature of all sign languages permits a precise quantitative analysis. As interest in visual electronic communication explodes within the deaf community, this work also paves the way for more precise automated sign recognition and synthesis.

In this article, it says:

We collected data using video logs (vlogs) from on-line sources such as YouTube.com, deafvideo.tv, and deafread.com. Video logs have become very popular in the Deaf community, due to the rise of fast Flash-based video sites like YouTube.com and due to the fact that vlogs allow signers to communicate visually.

Basically, the whole research comes up with the conclusion: ASL communication is as fast as spoken language!

To read this journal article, click HERE.

To read an article about this research on Technology Review: click HERE.

To summarize this… the time we spent by expressing ourselves in American Sign Language through vlogs, it was WORTH OUR TIME! Because there are people out there are very curious about our language and that helped to promote American Sign Language in many ways!

Yoohooo!

Amy Cohen Efron