Language in context seminar
Speaker: Nina Markl (University of Edinburgh)
Title: "Hey Siri, why don't you understand me?" Speech and Language Technologies, Language Variation & Algorithmic Bias
Abstract: In this talk, I'll explore how and why speech and language technologies are so bad at understanding so many of us, how that relates to the much larger problem of algorithmic bias in machine learning technologies, and what we, as users and developers of language(s) and technologies, could do to improve this situation.
Speech and language technologies (SLTs), such as automatic speech recognition, sentiment analysis and machine translation have become ubiquitous. These innovations, while often framed as convenient and (comparatively) cheap ways of increasing accessibility of computing technologies and information, only work for a very select group of language varieties. Many languages have little to no SLT support and within languages which have SLTs, these are much less “accurate” for marginalised user and language communities. In my research, I use methods and theories from a range of fields including sociolinguistics, phonetics, human-computer interaction, natural language processing, fairness and ethics in AI, critical data studies and feminist studies to understand not just "how bad" the bias is, or how we could develop a "technical fix" but also, what practises and ideologies underpin these technologies to understand how we got here in the first place.
Speaker bio: Nina is a third year PhD student in sociolinguistics and NLP in the CDT for NLP at the University of Edinburgh. Her research looks at the intersection of language variation and language technologies. Twitter: @ninamarkl, website: ninamarkl.github.io
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Co-ordinators of LinC
Language in context seminar
Online via link invitation