=Paper=
{{Paper
|id=Vol-3315/invited03
|storemode=property
|title=Can You Do Linguistics With Deep Learning? (invited talk)
|pdfUrl=https://ceur-ws.org/Vol-3315/invited03.pdf
|volume=Vol-3315
|authors=Mans Hulden
}}
==Can You Do Linguistics With Deep Learning? (invited talk)==
<pdf width="1500px">https://ceur-ws.org/Vol-3315/invited03.pdf</pdf>
<pre>
Can You Do Linguistics With Deep Learning?
Mans Hulden 1
1
    University of Colorado Boulder, USA


                                         Abstract
                                         Mans Hulden received his PhD in Linguistics from the University of Arizona in 2009. He joined the
                                         CU linguistics faculty in 2014 after postdoctoral research as a Marie Curie fellow at the University of
                                         Helsinki and a stint as visiting professor in Computer Science at the University of the Basque Country.
                                         His research focuses on developing computational methods to infer and model linguistic structure using
                                         varying degrees of prior linguistic knowledge, particularly in the domains of phonology and morphology.
                                         Dr. Hulden has worked extensively with linguistic applications of finite state technology, modeling of
                                         linguistic theory, grammatical inference, and the development of language resources, and is the author
                                         of several open-source tools for finite-state language modeling. He teaches courses in computational
                                         linguistics, phonology, and phonetics.




The International Conference and Workshop on Agglutinative Language Technologies as a challenge of Natural
Language Processing, ALTNLP’22, June 7-8, Koper, Slovenia
Envelope-Open mhulden@email.arizona.edu (M. H. )
                                       © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
    CEUR
    Workshop
    Proceedings
                  http://ceur-ws.org
                  ISSN 1613-0073
                                       CEUR Workshop Proceedings (CEUR-WS.org)

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