This paper presents our approach to automatic recognition of prosodic forms. In particular, we present: CALLIOPE, a multi-dimensional model aiming at categorizing 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 planning for investigating main acoustic behaviours and features involved into the discrimination of prosodic forms. The results of the experiment will be useful for defining the acoustic/textual features to rely on for automatic recognition of prosodic forms. 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.
Verso il riconoscimento automatico della prosodia
Roberto Tedesco;Sonia Cenceschi;Licia Sbattella
2018-01-01
Abstract
This paper presents our approach to automatic recognition of prosodic forms. In particular, we present: CALLIOPE, a multi-dimensional model aiming at categorizing 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 planning for investigating main acoustic behaviours and features involved into the discrimination of prosodic forms. The results of the experiment will be useful for defining the acoustic/textual features to rely on for automatic recognition of prosodic forms. 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.File | Dimensione | Formato | |
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