Improving the Performance of an In-Home Acoustic Monitoring System by Integrating a Vocal Effort Classification Algorithm

Principi E, Bonfigli R, Squartini S, Piazza F. Improving the Performance of an In-Home Acoustic Monitoring System by Integrating a Vocal Effort Classification Algorithm. In: AES Convention 136. Audio Engineering Society; 2014. Paper 9089. Available from: https://aes.org/publications/elibrary-page/?id=17235

@inproceedings{Principi2014_17235,
  author = {Principi, Emanuele and Bonfigli, Roberto and Squartini, Stefano and Piazza, Francesco},
  title = {{Improving the Performance of an In-Home Acoustic Monitoring System by Integrating a Vocal Effort Classification Algorithm}},
  booktitle = {AES Convention 136},
  note = {Paper 9089},
  year = {2014},
  month = apr,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=17235}
}

TY  - CPAPER
TI  - Improving the Performance of an In-Home Acoustic Monitoring System by Integrating a Vocal Effort Classification Algorithm
AU  - Principi, Emanuele
AU  - Bonfigli, Roberto
AU  - Squartini, Stefano
AU  - Piazza, Francesco
T2  - AES Convention 136
M1  - Paper 9089
PY  - 2014
DA  - 2014/04/06
UR  - https://aes.org/publications/elibrary-page/?id=17235
PB  - Audio Engineering Society
LA  - en
AB  - The research interest in technologies for supporting people in their own homes is constantly increasing. In this context this paper proposes a speech-interfaced system for recognizing home automation commands and distress calls. The robustness of the system is increased by employing Power Normalized Cepstral Coefficients as features and by using an adaptive algorithm to reduce known sources of interference. In addition, the mismatch introduced by vocal effort variability is reduced employing a vocal effort classifier and multiple acoustic models. The performance has been evaluated on ITAAL, a recently proposed corpus of home automation commands and distress calls in Italian. The results confirm that the adopted solutions are effective to be employed in a distorted acoustic scenario.
ER  -