Nowadays, dysarthric speech processing represents a challenge in assistive technology contexts. In this paper, we investigate the use of machine learning in conjunction with convolutional neural networks to implement a speaker dependent solution that is capable to detect just a few number of predefined keywords. The proposed system has been trained with utterances from Italian users with severe and mild dysarthria and it is configurable according to specific users’ preferences.

Machine learning in assistive technology: A solution for people with dysarthria

Mulfari D.;Meoni G.;Fanucci L.
2018-01-01

Abstract

Nowadays, dysarthric speech processing represents a challenge in assistive technology contexts. In this paper, we investigate the use of machine learning in conjunction with convolutional neural networks to implement a speaker dependent solution that is capable to detect just a few number of predefined keywords. The proposed system has been trained with utterances from Italian users with severe and mild dysarthria and it is configurable according to specific users’ preferences.
2018
Mulfari, D.; Meoni, G.; Fanucci, L.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1019565
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 8
  • ???jsp.display-item.citation.isi??? 7
social impact