Towards Automatic Recognition of Prosody

Abstract

The term prosody defines the group of audio paralinguistic and suprasegmental cues involved in the communicative and understanding process of human speech. This paper presents our approach to automatic recognition of prosodic forms. In particular, we present: CALLIOPE, a multi-dimensional and abstract model, aiming at categorising all prosodic forms; SI-CALLIOPE, a sub-space for which we defined a corpus of recorder prosodic forms; and the psychoacoustic experiment we are currently carrying on for investigating main acoustic behaviours and features involved into the discrimination of prosodic forms. The experiment results will be useful for defining the feature set to rely on for automatic recognition of prosodies. For that reason, we are also defining a classifier, based on Neural Nets. This study is part of the LYV project, which focuses on improving prosodic expressiveness skills of Italian speakers with autism and other cognitive disabilities.

Corrective Focus Detection in Italian Speech Using Neural Networks

“…The Corpus selected to carry out the proposed series of experiments is based on CALLIOPE (Combined and Assessed List of Latent Influences On Prosodic Expressivity), a conceptual model created within the LYV project 3 aiming at categorizing all IUs. Each IU is thus associated to a ''point'' into this space and associated to a tuple composed of 12 labels (detailed descriptions in [10]). In this multidimensional space each dimension represents a characteristic influencing the vocal paralinguistic components of the speech assuming values in a set of labels.…”

“…The experimental evaluation of the proposal was carried out over a subset of Italian Intonational Units based on the CALLIOPE Corpus [10,11]. This corpus aims at cataloging IUs from an acoustic point of view, which agrees with our goal to investigate the prosody.…”