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Digital Object Identifier 10.1109/MSP.2014.2369531

Date of publication: 12 February 2015

lexible and efficient spatial sound acquisition and subse-

quent processing are of paramount importance in com-

munication and assisted listening devices such as mobile

phones, hearing aids, smart TVs, and emerging wearable

devices (e.g., smart watches and glasses). In application

scenarios where the number of sound sources quickly varies,

sources move, and nonstationary noise and reverberation are

commonly encountered, it remains a challenge to capture sounds

in such a way that they can be reproduced with a high and invari-

able sound quality. In addition, the objective in terms of what

needs to be captured, and how it should be reproduced, depends

on the application and on the user’s preferences. Parametric spa-

tial sound processing has been around for two decades and

provides a flexible and efficient solution to capture, code, and

transmit, as well as manipulate and reproduce spatial sounds.

Instrumental to this type of processing is a parametric model

that can describe a sound field in a compact and general way. In

most cases, the sound field can be decomposed into a direct

sound component and a diffuse sound component. These two

components together with parametric side information such as

the direction-of-arrival (DOA) of the direct sound component or the

position of the sound source, provide a perceptually motivated

description of the acoustic scene [1]–[3]. In this article, we provide an

overview of recent advances in spatial sound capturing, manipula-

tion, and reproduction based on such parametric descriptions of the

sound field. In particular, we focus on two established parametric

descriptions presented in a unified way and show how the signals and

parameters can be obtained using multiple microphones. Once the

sound field is analyzed, the sound scene can be transmitted, manipu-

lated, and synthesized depending on the application. For example,

EARPHONES—IMAGE LICENSED BY INGRAM PUBLISHING

[

Konrad Kowalczyk, Oliver Thiergart, Maja Taseska,

Giovanni Del Galdo, Ville Pulkki, and Emanuël A.P. Habets

]

[

A flexible and efficient solution to sound scene

acquisition, modification, and reproduction

]

Parametric Spatial

Sound Processing

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