Prosodic prominence, a speech phenomenon by which some linguistic units are perceived as standing out from their environment, plays a very important role in human communication. In this paper we present a study on automatic prominence identification using Probabilistic Graphical Models, a family of Machine Learning Systems able to properly handle sequences of events. We tested the most promising members of such models on utterances selected from a manually annotated Italian speech corpus, obtaining very good recognition results crucially converging with the prominence detection responses provided by a pool of native speakers.

Prosodic prominence detection in Italian continuous speech using probabilistic graphical models

TAMBURINI, FABIO;
2014

Abstract

Prosodic prominence, a speech phenomenon by which some linguistic units are perceived as standing out from their environment, plays a very important role in human communication. In this paper we present a study on automatic prominence identification using Probabilistic Graphical Models, a family of Machine Learning Systems able to properly handle sequences of events. We tested the most promising members of such models on utterances selected from a manually annotated Italian speech corpus, obtaining very good recognition results crucially converging with the prominence detection responses provided by a pool of native speakers.
Social and Linguistic Speech Prosody. Proceedings of the 7th international conference on Speech Prosody
285
289
Tamburini F.; Bertini C.; Bertinetto P.M.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/479973
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