Pomante, L. and Santic, M. (2016) Methodologies, Tools and Technologies for Location-Aware AAL. IEEE 2nd International Forum on Research and Technologies for Society and Industry Leveraging a Better Tomorrow (RTSI), Bologna, 7-9 September 2016, 1-4.
https://doi.org/10.1109/RTSI.2016.7740566

has been cited by the following article:

• TITLE: BigEar: Ubiquitous Wireless Low-Budget Speech Capturing Interface

  AUTHORS: Stefano Gorla, Sara Comai, Andrea Masciadri, Fabio Salice

  KEYWORDS: Wireless Sensor Networks, Speech Capture, Degraded Speech Recognition, Ubiquitous Systems, Low Cost Architectures

  JOURNAL NAME: Journal of Computer and Communications, Vol.5 No.4, March 14, 2017

  ABSTRACT: This article presents BigEar, a wireless low-cost speech capturing interface that aims to realize unobtrusive and transparent context-aware vocal interaction for home automation. The speech recognition process implemented in BigEar system considers noise sources including possible holes in the reconstructed audio stream and tries to overcome them by means of inexactness toleration mechanisms to improve intelligibility of the reconstructed signal. Key contribution of this work is the use of extremely low cost devices to realize a modular flexible and real-time wireless sensor network. On-field implementation and experiments show that the proposed solution can perform real-time speech reconstruction, while listening tests confirm the intelligibility of the reconstructed signal.