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.
Titolo: | Prosodic prominence detection in Italian continuous speech using probabilistic graphical models |
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Titolo del libro: | Social and Linguistic Speech Prosody - Proceedings of the 7th International Conference on Speech Prosody 2014 |
Data di pubblicazione: | 2014 |
Nome del convegno: | 7th International Conference on Speech Prosody, SP 2014 |
Handle: | http://hdl.handle.net/11384/48099 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |