Comunicació presentada a: The 18th Annual Conference of the International Speech Communication Association (INTERSPEECH 2017), celebrada a Estocolm, Suència, del 20 al 24 d'agost de 2017.

This work aims to explore the correlation between the discourse structure of a spoken monologue and its prosody by predicting discourse relations from different prosodic attributes. For this purpose, a corpus of semi-spontaneous monologues in English has been automatically annotated according to the Rhetorical Structure Theory, which models coherence in text via rhetorical relations. From corresponding audio files, prosodic features such as pitch, intensity, and speech rate have been extracted from different contexts of a relation. Supervised classification tasks using Support Vector Machines have been performed to find relationships between prosodic features and rhetorical relations. Preliminary results show that intensity combined with other features extracted from intra- and intersegmental environments is the feature with the highest predictability for a discourse relation. The prediction of rhetorical relations from prosodic features and their combinations is straightforwardly applicable to several tasks such as speech understanding or generation. Moreover, the knowledge of how rhetorical relations should be marked in terms of prosody will serve as a basis to improve speech synthesis applications and make voices sound more natural and expressive.

This work is part of the KRISTINA project, which has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Grant Agreement number 645012. The second author is partially funded by the Spanish Ministry of Economy, Industry and Competitiveness through the Ramón y Cajal program. The third and fourth authors are partially funded by ANPCYT PICT 2014-1561, and the Air Force Office of Scientific Research, Air Force Material Command, USAF under Award No. FA9550-15-1-0055.