You are invited to participate in our discussion this week, Tuesday, November 9, 2-5pm EST, on “Linguistics and Social Justice: Language, Education & Human Rights” (MIT Linguistics, Graduate Seminar, 24.S96). Please contact Michel <degraff@mit.edu> for information about Zoom link and readings. NB: We are committed to creating an inclusive and accessible environment in our seminar. If you need assistance for accommodations or accessibility in order to fully participate, please email degraff@MIT.EDU so that we can work out adequate arrangements.
This Tuesday, November 16, 2021, Kevin Scannell will help us understand the potential of digital technology for deminoritizing, revitalizing and normalizing endangered languages — and other kinds of minoritized languages:
Language from Below:
Grassroots efforts to develop language technology for minoritized languages
Kevin Scannell
November 16, 2021, 2-5pm EST
Seminar: “Linguistics & social justice” (24.S96 @ MIT Linguistics)
Technology plays a key role in revitalization efforts in many language communities. Without the ability to use one’s native language on computers, mobile devices, social media sites, etc., speakers are forced to shift to a dominant language in contexts where computing plays an important role, most notably in schools and in the workplace.
Kevin Scannell is professor of mathematics and computer science at Saint Louis University. He works with language communities around the world to develop computing resources that help them use their native language online, with a particular focus on Irish and the other Celtic languages.
On Tuesday, November 16, he will share some success stories in developing language technology — both in his own work on Irish in Ireland, and in the work of his friends and collaborators on the Māori language in Aotearoa / New Zealand.
Successes in Ireland have been achieved in the face of some huge obstacles: little or no funding for these initiatives, general disinterest from the big tech companies, a very fast-moving software landscape, and technical challenges that arise when applying machine learning approaches to languages that lack sufficiently-large datasets for training.
For Irish, some of these obstacles have been overcome through a community-based, grassroots approach to tech development, and occasional (sometimes uneasy) collaborations with big tech.
Kevin and colleagues’ work in Ireland can be viewed as part of a long history of language activism “from below.”