A Speech-Based System for In-Home Emergency Detection and Remote Assistance
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E. Principi, D. Fuselli, S. Squartini, M. Bonifazi, and F. Piazza, "A Speech-Based System for In-Home Emergency Detection and Remote Assistance," Paper 8828, (2013 May.). doi:
E. Principi, D. Fuselli, S. Squartini, M. Bonifazi, and F. Piazza, "A Speech-Based System for In-Home Emergency Detection and Remote Assistance," Paper 8828, (2013 May.). doi:
Abstract: This paper describes a system for the detection of emergency states and for the remote assistance of people in their own homes. Emergencies are detected recognizing distress calls by means of a speech recognition engine. When an emergency is detected, a phone call is automatically established with a relative or friend by means of a VoIP stack and an Acoustic Echo Canceller. Several low-consuming embedded units are distributed throughout the house to monitor the acoustic environment, and one central unit coordinates the system operation. This unit also integrates multimedia content delivery services and home automation functionalities. Being an ongoing project, this paper describes the entire system and then focuses on the algorithms implemented for the acoustic monitoring and the hands-free communication services. Preliminary experiments have been conducted to assess the performance of the recognition module in noisy and reverberated environments and the out of grammar rejection capabilities. Results showed that the implemented Power Normalized Cepstral Coefficients extraction pipeline improves the word recognition accuracy in noisy and reverberated conditions, and that introducing a "garbage phone" in the acoustic model allows to effectively reject out of grammar words and sentences.
@article{principi2013a,
author={principi, emanuele and fuselli, danilo and squartini, stefano and bonifazi, maurizio and piazza, francesco},
journal={journal of the audio engineering society},
title={a speech-based system for in-home emergency detection and remote assistance},
year={2013},
volume={},
number={},
pages={},
doi={},
month={may},}
@article{principi2013a,
author={principi, emanuele and fuselli, danilo and squartini, stefano and bonifazi, maurizio and piazza, francesco},
journal={journal of the audio engineering society},
title={a speech-based system for in-home emergency detection and remote assistance},
year={2013},
volume={},
number={},
pages={},
doi={},
month={may},
abstract={this paper describes a system for the detection of emergency states and for the remote assistance of people in their own homes. emergencies are detected recognizing distress calls by means of a speech recognition engine. when an emergency is detected, a phone call is automatically established with a relative or friend by means of a voip stack and an acoustic echo canceller. several low-consuming embedded units are distributed throughout the house to monitor the acoustic environment, and one central unit coordinates the system operation. this unit also integrates multimedia content delivery services and home automation functionalities. being an ongoing project, this paper describes the entire system and then focuses on the algorithms implemented for the acoustic monitoring and the hands-free communication services. preliminary experiments have been conducted to assess the performance of the recognition module in noisy and reverberated environments and the out of grammar rejection capabilities. results showed that the implemented power normalized cepstral coefficients extraction pipeline improves the word recognition accuracy in noisy and reverberated conditions, and that introducing a "garbage phone" in the acoustic model allows to effectively reject out of grammar words and sentences.},}
TY - paper
TI - A Speech-Based System for In-Home Emergency Detection and Remote Assistance
SP -
EP -
AU - Principi, Emanuele
AU - Fuselli, Danilo
AU - Squartini, Stefano
AU - Bonifazi, Maurizio
AU - Piazza, Francesco
PY - 2013
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2013
TY - paper
TI - A Speech-Based System for In-Home Emergency Detection and Remote Assistance
SP -
EP -
AU - Principi, Emanuele
AU - Fuselli, Danilo
AU - Squartini, Stefano
AU - Bonifazi, Maurizio
AU - Piazza, Francesco
PY - 2013
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2013
AB - This paper describes a system for the detection of emergency states and for the remote assistance of people in their own homes. Emergencies are detected recognizing distress calls by means of a speech recognition engine. When an emergency is detected, a phone call is automatically established with a relative or friend by means of a VoIP stack and an Acoustic Echo Canceller. Several low-consuming embedded units are distributed throughout the house to monitor the acoustic environment, and one central unit coordinates the system operation. This unit also integrates multimedia content delivery services and home automation functionalities. Being an ongoing project, this paper describes the entire system and then focuses on the algorithms implemented for the acoustic monitoring and the hands-free communication services. Preliminary experiments have been conducted to assess the performance of the recognition module in noisy and reverberated environments and the out of grammar rejection capabilities. Results showed that the implemented Power Normalized Cepstral Coefficients extraction pipeline improves the word recognition accuracy in noisy and reverberated conditions, and that introducing a "garbage phone" in the acoustic model allows to effectively reject out of grammar words and sentences.
This paper describes a system for the detection of emergency states and for the remote assistance of people in their own homes. Emergencies are detected recognizing distress calls by means of a speech recognition engine. When an emergency is detected, a phone call is automatically established with a relative or friend by means of a VoIP stack and an Acoustic Echo Canceller. Several low-consuming embedded units are distributed throughout the house to monitor the acoustic environment, and one central unit coordinates the system operation. This unit also integrates multimedia content delivery services and home automation functionalities. Being an ongoing project, this paper describes the entire system and then focuses on the algorithms implemented for the acoustic monitoring and the hands-free communication services. Preliminary experiments have been conducted to assess the performance of the recognition module in noisy and reverberated environments and the out of grammar rejection capabilities. Results showed that the implemented Power Normalized Cepstral Coefficients extraction pipeline improves the word recognition accuracy in noisy and reverberated conditions, and that introducing a "garbage phone" in the acoustic model allows to effectively reject out of grammar words and sentences.
Authors:
Principi, Emanuele; Fuselli, Danilo; Squartini, Stefano; Bonifazi, Maurizio; Piazza, Francesco
Affiliations:
Universitá Politecnica delle Marche, Ancona, Italy; FBT Elettronica Spa, Recanti (MC), Italy(See document for exact affiliation information.)
AES Convention:
134 (May 2013)
Paper Number:
8828
Publication Date:
May 4, 2013Import into BibTeX
Subject:
Speech Processing
Permalink:
http://www.aes.org/e-lib/browse.cfm?elib=16729