University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Audio Inpainting

Adler, A, Emiya, V, Jafari, MG, Elad, M, Gribonval, R and Plumbley, MD (2012) Audio Inpainting IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 20 (3). pp. 922-932.

[img]
Preview
Text
AdlerEmiyaJafariEGP12-audio-inpainting_accepted.pdf - Accepted version Manuscript
Available under License : See the attached licence file.

Download (442kB) | Preview
[img]
Preview
PDF (licence)
SRI_deposit_agreement.pdf
Available under License : See the attached licence file.

Download (33kB) | Preview

Abstract

We propose the audio inpainting framework that recovers portions of audio data distorted due to impairments such as impulsive noise, clipping, and packet loss. In this framework, the distorted data are treated as missing and their location is assumed to be known. The signal is decomposed into overlapping time-domain frames and the restoration problem is then formulated as an inverse problem per audio frame. Sparse representation modeling is employed per frame, and each inverse problem is solved using the Orthogonal Matching Pursuit algorithm together with a discrete cosine or a Gabor dictionary. The Signal-to-Noise Ratio performance of this algorithm is shown to be comparable or better than state-of-the-art methods when blocks of samples of variable durations are missing. We also demonstrate that the size of the block of missing samples, rather than the overall number of missing samples, is a crucial parameter for high quality signal restoration. We further introduce a constrained Matching Pursuit approach for the special case of audio declipping that exploits the sign pattern of clipped audio samples and their maximal absolute value, as well as allowing the user to specify the maximum amplitude of the signal. This approach is shown to outperform state-of-the-art and commercially available methods for audio declipping in terms of Signal-to-Noise Ratio

Item Type: Article
Subjects : Signal Processing
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
AuthorsEmailORCID
Adler, AUNSPECIFIEDUNSPECIFIED
Emiya, VUNSPECIFIEDUNSPECIFIED
Jafari, MGUNSPECIFIEDUNSPECIFIED
Elad, MUNSPECIFIEDUNSPECIFIED
Gribonval, RUNSPECIFIEDUNSPECIFIED
Plumbley, MDUNSPECIFIEDUNSPECIFIED
Date : 1 March 2012
Identification Number : 10.1109/TASL.2011.2168211
Copyright Disclaimer : © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords : Science & Technology, Technology, Acoustics, Engineering, Electrical & Electronic, Engineering, ACOUSTICS, ENGINEERING, ELECTRICAL & ELECTRONIC, Clipping, inpainting, matching pursuit (MP), sparse representation (SR), MATCHING PURSUIT, SPARSE REPRESENTATION, INTERPOLATION, DICTIONARIES, RESTORATION, RECOVERY, SIGNALS, MODEL, PREDICTION
Related URLs :
Additional Information : © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Symplectic Elements
Date Deposited : 22 Mar 2016 15:57
Last Modified : 24 Mar 2016 09:40
URI: http://epubs.surrey.ac.uk/id/eprint/810156

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800