| dc.contributor.author | Lafay, G | |
| dc.contributor.author | Lagrange, M | |
| dc.contributor.author | Rossignol, M | |
| dc.contributor.author | BENETOS, E | |
| dc.contributor.author | Roebel, A | |
| dc.date.accessioned | 2016-07-11T13:05:14Z | |
| dc.date.available | 2016-07-11T13:05:14Z | |
| dc.date.issued | 2016-07 | |
| dc.date.submitted | 2016-07-03T09:46:56.942Z | |
| dc.identifier.citation | Lafay, Greoigre, Mathieu Lagrange, Emmanouil Benetos, Mathias Rossignol, and Axel Roebel, "A Morphological Model For Simulating Acoustic Scenes And Its Application To Sound Event Detection", IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2016, 1-1 <http://dx.doi.org/10.1109/taslp.2016.2587218> | en_US |
| dc.identifier.uri | http://qmro.qmul.ac.uk/xmlui/handle/123456789/13423 | |
| dc.description.abstract | This paper introduces a model for simulating environmental acoustic scenes that abstracts temporal structures from audio recordings. This model allows us to explicitly control key morphological aspects of the acoustic scene and to isolate their impact on the performance of the system under evaluation. Thus, more information can be gained on the behavior of an evaluated system, providing guidance for further improvements. To demonstrate its potential, this model is employed to evaluate the performance of nine state of the art sound event detection systems submitted to the IEEE DCASE 2013 Challenge. Results indicate that the proposed scheme is able to successfully build datasets useful for evaluating important aspects of the performance of sound event detection systems, such as their robustness to new recording conditions and to varying levels of background audio. | en_US |
| dc.description.sponsorship | This paper introduces a model for simulating environmental acoustic scenes that abstracts temporal structures from audio recordings. This model allows us to explicitly control key morphological aspects of the acoustic scene and to isolate their impact on the performance of the system under evaluation. Thus, more information can be gained on the behavior of an evaluated system, providing guidance for further improvements. To demonstrate its potential, this model is employed to evaluate the performance of nine state of the art sound event detection systems submitted to the IEEE DCASE 2013 Challenge. Results indicate that the proposed scheme is able to successfully build datasets useful for evaluating important aspects of the performance of sound event detection systems, such as their robustness to new recording conditions and to varying levels of background audio. | en_US |
| dc.publisher | IEEE | en_US |
| dc.relation.isreplacedby | 123456789/17621 | |
| dc.relation.isreplacedby | http://qmro.qmul.ac.uk/xmlui/handle/123456789/17621 | |
| dc.rights | • © 20xx 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. | |
| dc.title | A morphological model for simulating acoustic scenes and its application to sound event detection | en_US |
| dc.type | Article | en_US |
| dc.identifier.doi | 10.1109/TASLP.2016.2587218 | |
| dc.relation.isPartOf | IEEE/ACM Transactions on Audio, Speech, and Language Processing | |
| pubs.publication-status | Accepted | |
| pubs.publisher-url | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7503122 | |
