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How Language Became Data: Speech Recognition Between Likeness and Likelihood

Date and Time: 
Tuesday, May 26, 2020. 05:00 PM - 07:00 PM
Meeting Location: 
Zoom
Workshop: 
Digital Aesthetics: Critical Approaches to Computational Culture 2019
Meeting Description: 

Xiaochang Li will share new research on the history of automatic speech recognition technologies. Beginning in 1971, a team of researchers at IBM began to reorient the field of automatic speech recognition away from the study of human speech and language and towards a startling new mandate: “There’s no data like more data.” In the ensuing decades, speech recognition was refashioned as a problem of large-scale data acquisition and classification, one that was distinct from, if not antithetical to, explanation, interpretability, and expertise. The history of automatic speech recognition invites a glimpse into how making language into data helped make data into an imperative, opening the door for the expansion of algorithmic culture into everyday life.

Xiaochang Li is an Assistant Professor of Communication at Stanford University. Her research examines questions surrounding the relationship between information technology and knowledge production and its role in the organization of social life.

Email Jeff Nagy (jsnagy@stanford.edu) by May 25th for Zoom link.

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