Localising speech, footsteps and other sounds using resource-constrained devices

While a number of acoustic localisation systems have been proposed over the last few decades, these have typically either relied on expensive dedicated microphone arrays and workstation-class processing, or have been developed to detect a very specific type of sound in a particular scenario. However...

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Published in:2011 10th International Conference on Information Processing in Sensor Networks pp. 330 - 341
Main Authors: Yukang Guo, Hazas, M
Format: Conference Proceeding
Language:English
Published: IEEE 01.04.2011
Subjects:
Acoustics
Algorithm design and analysis
Design
Estimation
Experimentation
Feature extraction
General Terms-Algorithms
Measurement
Microphones
Noise
Speech
ISBN:9781612848549, 1612848540
Online Access:Get full text
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Abstract While a number of acoustic localisation systems have been proposed over the last few decades, these have typically either relied on expensive dedicated microphone arrays and workstation-class processing, or have been developed to detect a very specific type of sound in a particular scenario. However, as people live and work indoors, they generate a wide variety of sounds as they interact and move about. These human-generated sounds can be used to infer the positions of people, without requiring them to wear trackable tags. In this paper, we take a practical yet general approach to localising a number of human-generated sounds. Drawing from signal processing literature, we identify methods for resource-constrained devices in a sensor network to detect, classify and locate acoustic events such as speech, footsteps and objects being placed onto tables. We evaluate the classification and time-of-arrival estimation algorithms using a data set of human-generated sounds we captured with sensor nodes in a controlled setting. We show that despite the variety and complexity of the sounds, their localisation is feasible for sensor networks, with typical accuracies of a half metre or better. We specifically discuss the processing and networking considerations, and explore the performance trade-offs which can be made to further conserve resources.
AbstractList While a number of acoustic localisation systems have been proposed over the last few decades, these have typically either relied on expensive dedicated microphone arrays and workstation-class processing, or have been developed to detect a very specific type of sound in a particular scenario. However, as people live and work indoors, they generate a wide variety of sounds as they interact and move about. These human-generated sounds can be used to infer the positions of people, without requiring them to wear trackable tags. In this paper, we take a practical yet general approach to localising a number of human-generated sounds. Drawing from signal processing literature, we identify methods for resource-constrained devices in a sensor network to detect, classify and locate acoustic events such as speech, footsteps and objects being placed onto tables. We evaluate the classification and time-of-arrival estimation algorithms using a data set of human-generated sounds we captured with sensor nodes in a controlled setting. We show that despite the variety and complexity of the sounds, their localisation is feasible for sensor networks, with typical accuracies of a half metre or better. We specifically discuss the processing and networking considerations, and explore the performance trade-offs which can be made to further conserve resources.
Author Yukang Guo
Hazas, M
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  organization: Sch. of Comput. & Commun., Lancaster Univ., Lancaster, UK
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Snippet While a number of acoustic localisation systems have been proposed over the last few decades, these have typically either relied on expensive dedicated...
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StartPage 330
SubjectTerms Acoustics
Algorithm design and analysis
Design
Estimation
Experimentation
Feature extraction
General Terms-Algorithms
Measurement
Microphones
Noise
Speech
Title Localising speech, footsteps and other sounds using resource-constrained devices
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