This paper describes a system for recognizing distress calls and home automation voice commands in a smart-home. Distress calls are recognized with the purpose of assisting people in their own homes: when they are detected, a phone call is automatically established with a contact in a address book and the person can request for assistance. The voice call is established through a voice over ip stack, with hands-free communication guaranteed by an acoustic echo canceller. The acoustic environment is constantly monitored by several low-consuming devices distributed throughout the home. In each device, a voice activity detector detects speech segments, and a speech recognition engine recognizes commands and distress calls. Robustness to environmental disturbances has been increased by employing Power Normalized Cepstral Coefficients and by using an adaptive algorithm for interference cancellation. An Italian speech corpus of home automation commands and distress calls has been developed for evaluation purposes. The corpus has been recorded in a real room using multiple microphones, and each sentence has been uttered both in normal and shouted speaking styles. The system performance has been assessed in terms of commands/distress recognition accuracy in order to prove the effectiveness of the approach.

A distributed system for recognizing home automation commands and distress calls in the Italian language

PRINCIPI, EMANUELE;SQUARTINI, Stefano;PIAZZA, Francesco;
2013-01-01

Abstract

This paper describes a system for recognizing distress calls and home automation voice commands in a smart-home. Distress calls are recognized with the purpose of assisting people in their own homes: when they are detected, a phone call is automatically established with a contact in a address book and the person can request for assistance. The voice call is established through a voice over ip stack, with hands-free communication guaranteed by an acoustic echo canceller. The acoustic environment is constantly monitored by several low-consuming devices distributed throughout the home. In each device, a voice activity detector detects speech segments, and a speech recognition engine recognizes commands and distress calls. Robustness to environmental disturbances has been increased by employing Power Normalized Cepstral Coefficients and by using an adaptive algorithm for interference cancellation. An Italian speech corpus of home automation commands and distress calls has been developed for evaluation purposes. The corpus has been recorded in a real room using multiple microphones, and each sentence has been uttered both in normal and shouted speaking styles. The system performance has been assessed in terms of commands/distress recognition accuracy in order to prove the effectiveness of the approach.
2013
9781629934433
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/112686
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