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 F.; Bertini C.; Bertinetto P.M.. - ELETTRONICO. - 1:1(2014), pp. 285-289. (Intervento presentato al convegno Speech Prosody 7 tenutosi a Dublin nel 20-23 maggio 2014).
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.