Audio coding in wireless acoustic sensor networks

Research output: Contribution to journalJournal articleResearchpeer-review

10 Citations (Scopus)

Abstract

In this paper, we consider the problem of source coding for a wireless acoustic sensor network where each node in the network makes its own noisy measurement of the sound field, and communicates with other nodes in the network by sending and receiving encoded versions of the measurements. To make use of the correlation between the sources available at the nodes, we consider the possibility of combining the measurement and the received messages into one single message at each node instead of forwarding the received messages and separate encoding of the measurement. Moreover, to exploit the correlation between the messages received by a node and the node's measurement of the source, we propose to use the measurement as side information and thereby form a distributed source coding (DSC) problem. Assuming that the sources are Gaussian, we then derive the rate-distortion function (RDF) for the resulting remote DSC problem under covariance matrix distortion constraints. We further show that for this problem, the Gaussian source is the worst to code. Thus, the Gaussian RDF provides an upper bound to other sources such as audio signals. We then turn our attention to audio signals. We consider an acoustical model based on the room impulse response (RIR) and provide simulation results for the rate-distortion performance in a practical setup where a set of microphones record the sound in a standard listening room. Since our reconstruction scheme and distortion measure are defined over the direct sound source, coding and dereverberation are performed in a joint manner.
Original languageEnglish
JournalSignal Processing
Volume107
Pages (from-to)141-152
Number of pages12
ISSN0165-1684
DOIs
Publication statusPublished - 2015

Fingerprint

Sensor networks
Acoustics
Acoustic waves
Acoustic fields
Microphones
Covariance matrix
Impulse response

Cite this

@article{061e9b6ae9854e0293ef324730ddff7d,
title = "Audio coding in wireless acoustic sensor networks",
abstract = "In this paper, we consider the problem of source coding for a wireless acoustic sensor network where each node in the network makes its own noisy measurement of the sound field, and communicates with other nodes in the network by sending and receiving encoded versions of the measurements. To make use of the correlation between the sources available at the nodes, we consider the possibility of combining the measurement and the received messages into one single message at each node instead of forwarding the received messages and separate encoding of the measurement. Moreover, to exploit the correlation between the messages received by a node and the node's measurement of the source, we propose to use the measurement as side information and thereby form a distributed source coding (DSC) problem. Assuming that the sources are Gaussian, we then derive the rate-distortion function (RDF) for the resulting remote DSC problem under covariance matrix distortion constraints. We further show that for this problem, the Gaussian source is the worst to code. Thus, the Gaussian RDF provides an upper bound to other sources such as audio signals. We then turn our attention to audio signals. We consider an acoustical model based on the room impulse response (RIR) and provide simulation results for the rate-distortion performance in a practical setup where a set of microphones record the sound in a standard listening room. Since our reconstruction scheme and distortion measure are defined over the direct sound source, coding and dereverberation are performed in a joint manner.",
author = "Adel Zahedi and Jan {\O}stergaard and Jensen, {S{\o}ren Holdt} and S{\o}ren Bech and Patrick Naylor",
year = "2015",
doi = "10.1016/j.sigpro.2014.07.021",
language = "English",
volume = "107",
pages = "141--152",
journal = "Signal Processing",
issn = "0165-1684",
publisher = "Elsevier",

}

Audio coding in wireless acoustic sensor networks. / Zahedi, Adel; Østergaard, Jan; Jensen, Søren Holdt; Bech, Søren; Naylor, Patrick.

In: Signal Processing, Vol. 107, 2015, p. 141-152.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Audio coding in wireless acoustic sensor networks

AU - Zahedi, Adel

AU - Østergaard, Jan

AU - Jensen, Søren Holdt

AU - Bech, Søren

AU - Naylor, Patrick

PY - 2015

Y1 - 2015

N2 - In this paper, we consider the problem of source coding for a wireless acoustic sensor network where each node in the network makes its own noisy measurement of the sound field, and communicates with other nodes in the network by sending and receiving encoded versions of the measurements. To make use of the correlation between the sources available at the nodes, we consider the possibility of combining the measurement and the received messages into one single message at each node instead of forwarding the received messages and separate encoding of the measurement. Moreover, to exploit the correlation between the messages received by a node and the node's measurement of the source, we propose to use the measurement as side information and thereby form a distributed source coding (DSC) problem. Assuming that the sources are Gaussian, we then derive the rate-distortion function (RDF) for the resulting remote DSC problem under covariance matrix distortion constraints. We further show that for this problem, the Gaussian source is the worst to code. Thus, the Gaussian RDF provides an upper bound to other sources such as audio signals. We then turn our attention to audio signals. We consider an acoustical model based on the room impulse response (RIR) and provide simulation results for the rate-distortion performance in a practical setup where a set of microphones record the sound in a standard listening room. Since our reconstruction scheme and distortion measure are defined over the direct sound source, coding and dereverberation are performed in a joint manner.

AB - In this paper, we consider the problem of source coding for a wireless acoustic sensor network where each node in the network makes its own noisy measurement of the sound field, and communicates with other nodes in the network by sending and receiving encoded versions of the measurements. To make use of the correlation between the sources available at the nodes, we consider the possibility of combining the measurement and the received messages into one single message at each node instead of forwarding the received messages and separate encoding of the measurement. Moreover, to exploit the correlation between the messages received by a node and the node's measurement of the source, we propose to use the measurement as side information and thereby form a distributed source coding (DSC) problem. Assuming that the sources are Gaussian, we then derive the rate-distortion function (RDF) for the resulting remote DSC problem under covariance matrix distortion constraints. We further show that for this problem, the Gaussian source is the worst to code. Thus, the Gaussian RDF provides an upper bound to other sources such as audio signals. We then turn our attention to audio signals. We consider an acoustical model based on the room impulse response (RIR) and provide simulation results for the rate-distortion performance in a practical setup where a set of microphones record the sound in a standard listening room. Since our reconstruction scheme and distortion measure are defined over the direct sound source, coding and dereverberation are performed in a joint manner.

U2 - 10.1016/j.sigpro.2014.07.021

DO - 10.1016/j.sigpro.2014.07.021

M3 - Journal article

VL - 107

SP - 141

EP - 152

JO - Signal Processing

JF - Signal Processing

SN - 0165-1684

ER -