Disfluency prediction in natural spoken language

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Abstract: Until recently, disfluencies in human language were outside of the focus of linguistic research. However, with the advent of technologies such as digital personal assistants, this approach changed. In order to mimic natural conversation, it is necessary to create a natural sounding output, including phenomena deemed undesirable in an idealized view of the language, such as disfluencies. This thesis presents two novel approaches to disfluency prediction. It extends the list of known predictors of disfluencies with surprisal, a measure of processing complexity derived from psycholinguistic and information-theoretic observations. Additionally, it presents a computational-linguistic approach in which a machine translation architecture (encoder-decoder) is used for the prediction of disfluencies

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch
Anmerkungen
Universität Freiburg, Dissertation, 2019

Schlagwort
Englisch
Maschinelles Lernen
Verzögerungsphänomen
Korpus
Informationstheorie

Ereignis
Veröffentlichung
(wo)
Freiburg
(wer)
Universität
(wann)
2021
Urheber
Beteiligte Personen und Organisationen

DOI
10.6094/978-3-928969-84-0
URN
urn:nbn:de:bsz:25-freidok-2197227
Rechteinformation
Kein Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Letzte Aktualisierung
25.03.2025, 13:44 MEZ

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  • 2021

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