Does my Speech Rock? Automatic Assessment of Public Speaking Skills

Azais, Lucas, Payan, Adrien, Sun, Tianjiao, Vidal, Guillaume, Zhang, Tina, Coutinho, Eduardo ORCID: 0000-0001-5234-1497, Eyben, Florian and Schuller, Bjoern (2015) Does my Speech Rock? Automatic Assessment of Public Speaking Skills. , 2015-9-6 - 2015-9-10.

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Abstract

In this paper, we introduce results for the task of Automatic Public Speech Assessment (APSA). Given the comparably sparse work carried out on this task up to this point, a novel database was required for training and evaluation of machine learning models. As a basis, the freely available oral presentations of the ICASSP conference in 2011 were selected due to their transcription including non-verbal vocalisations. The data was specifically labelled in terms of the perceived oratory ability of the speakers by five raters according to a 5-point Public Speaking Skill Rating Likert scale. We investigate the feasibility of speaker-independent APSA using different standardised acoustic feature sets computed per fixed chunk of an oral presentation in a series of ternary classification and continuous regression experiments. Further, we compare the relevance of different feature groups related to fluency (speech/hesitation rate), prosody, voice quality and a variety of spectral features. Our results demonstrate that oratory speaking skills can be reliably assessed using suprasegmental audio features, with prosodic ones being particularly suited.

Item Type:	Conference or Workshop Item (Unspecified)
Additional Information:	(51\,% acceptance rate)
Uncontrolled Keywords:	Automatic Public Speech Assessment, database, classification, regression, prosody
Depositing User:	Symplectic Admin
Date Deposited:	18 Apr 2016 14:55
Last Modified:	16 Dec 2022 01:22
Related URLs:	Author
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3000594