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HOW CONFIDENT ARE YOU? EXPLORING THE ROLE OF FILLERS IN THE AUTOMATIC PREDICTION OF A SPEAKER’S CONFIDENCE

Abstract : "Fillers", example "um" in English, have been linked to the "Feeling of Another's Knowing (FOAK)" or the listener's perception of a speaker's expressed confidence. Yet, in Spoken Language Processing (SLP) they remain unexplored, or overlooked as noise. We introduce a new and challenging task, that is the prediction of FOAK, which we think has widespread applicability, given the increasing popularity of automatic processing of educational and job interviews, reviews and speeches. We design a set of filler features based on linguistic literature, and investigate their potential in FOAK prediction. We show that the integration of information related to implicature meanings allows an improvement in the FOAK model and that the different functions of fillers are differently correlated with confidence.
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Submitted on : Thursday, September 17, 2020 - 3:58:39 PM
Last modification on : Tuesday, November 16, 2021 - 4:35:52 AM
Long-term archiving on: : Thursday, December 3, 2020 - 10:13:33 AM

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Tanvi Dinkar, Ioana Vasilescu, Catherine Pelachaud, Chloé Clavel. HOW CONFIDENT ARE YOU? EXPLORING THE ROLE OF FILLERS IN THE AUTOMATIC PREDICTION OF A SPEAKER’S CONFIDENCE. ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2020, Barcelona, Spain. pp.8104-8108, ⟨10.1109/ICASSP40776.2020.9054374⟩. ⟨hal-02942182⟩

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