It’s relatively easy to trace a written linguistic history—there’s generally a lot of written documentation and records to study. Things get trickier, however, when attempting to examine a sign language’s evolution. Most transformations within the currently over 300 known sign languages (or SLs) around the world occurred sans text over generations of learners. Add in the centuries of marginalization experienced by Deaf and hard of hearing communities, and establishing concrete relationships between SLs becomes extremely difficult.
To help correct this long standing issue, researchers recently created a novel computational program capable of analyzing the relationships between various SLs. The result, published today in Science, is a first-of-its-kind large-scale study that greatly expands on linguists’ understanding of sign language development while challenging long held beliefs about its evolution.
[Related: Online classes are difficult for the hard of hearing. Here’s how to fix that.]
“Many people mistakenly think that sign language is shared around the world, but really the world is full of a vibrant tapestry of different sign languages,” Natasha Abner, study lead author and an associate professor of linguistics at the University of Michigan, writes in an email to PopSci.
For their study, Abner and her colleagues first compiled a video dictionary of core, “resilient” vocabulary across 19 modern sign languages, such as American, British, Chinese, French, Japanese, and Spanish, among others. For example, while a sign for “oak tree” may only occur in languages spoken in regions with oak trees, the concept of just a “tree” is much more ubiquitous. Researchers then broke down video demonstrations for the 19 signing variants for “tree” (along with many other words) into basic phonetic parameters, then entered it all into a massive database.
“What we do in the study is look at how the sign languages refer to these commonplace, universal objects in the world and we work backwards to build a history of the language and languages,” Abner says. “This built history helps us understand the histories of the communities in ways that the historical records cannot because they are so limited and sparse.”
The computational analysis program then examined the signed vocabulary glossary, categorizing each entry based on intricate factors like handedness (one- or two-handed signs), handshape, location, and movement.
“This coding system avoids outcomes driven by superficial similarities or differences in two key ways,” reads a portion of the team’s study. “One, possible character values in the coding system range from two distinct values (handedness) to 10 distinct values (handshape), so it is a highly articulated system capable of capturing and tracking fine-grained differences.”
In tracing signed vocabularies’ evolutions, researchers applied phylogenetic analysis typically associated with biologically inherited traits to physically conveyed communications.
“In our study, the ‘genes’ of language are the words that the languages use to describe the world around them,” says Abner.