Does my Speech Rock? Automatic Assessment of Public Speaking Skills. Payan, A., Sun, T., Vidal, G., Zhang, T., Coutinho, E., & Eyben, F. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, volume 1, pages 2519-2523, 2015. ISCA.
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Paper Website abstract bibtex 1 download 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 supra-segmental audio features, with prosodic ones being particularly suited.
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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 supra-segmental audio features, with prosodic ones being particularly suited.},
bibtype = {inproceedings},
author = {Payan, Adrien and Sun, Tianjiao and Vidal, Guillaume and Zhang, Tina and Coutinho, Eduardo and Eyben, Florian},
booktitle = {Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH}
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