Experimental studies using qualitative or quantitative analysis have demonstrated that the human voice progressively worsens with ageing. These studies, however, have mostly focused on specific voice features without examining their dynamic interaction. To examine the complexity of age-related changes in voice, more advanced techniques based on machine learning have been recently applied to voice recordings but only in a laboratory setting. We here recorded voice samples in a large sample of healthy subjects. To improve the ecological value of our analysis, we collected voice samples directly at home using smartphones.

Asci, F., Costantini, G., Di Leo, P., Zampogna, A., Ruoppolo, G., Berardelli, A., et al. (2020). Machine-learning analysis of voice samples recorded through smartphones: the combined effect of ageing and gender. SENSORS, 20(18) [10.3390/s20185022].

Machine-learning analysis of voice samples recorded through smartphones: the combined effect of ageing and gender

Costantini G.;Saggio G.;
2020-01-01

Abstract

Experimental studies using qualitative or quantitative analysis have demonstrated that the human voice progressively worsens with ageing. These studies, however, have mostly focused on specific voice features without examining their dynamic interaction. To examine the complexity of age-related changes in voice, more advanced techniques based on machine learning have been recently applied to voice recordings but only in a laboratory setting. We here recorded voice samples in a large sample of healthy subjects. To improve the ecological value of our analysis, we collected voice samples directly at home using smartphones.
2020
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore ING-IND/31 - ELETTROTECNICA
English
ageing; gender; machine learning; support vector machine; voice analysis
Asci, F., Costantini, G., Di Leo, P., Zampogna, A., Ruoppolo, G., Berardelli, A., et al. (2020). Machine-learning analysis of voice samples recorded through smartphones: the combined effect of ageing and gender. SENSORS, 20(18) [10.3390/s20185022].
Asci, F; Costantini, G; Di Leo, P; Zampogna, A; Ruoppolo, G; Berardelli, A; Saggio, G; Suppa, A
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/255044
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