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Martin Raspaud

dblp:02/8308 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2010
0000-0002-3221-3778ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Audio and music processing · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Audio and music processing › sound source localization
binaural localization		 0.112010
Binaural Source Localization by Joint Estimation of ILD and ITD · IEEE Trans. Speech Audio Process. 2010
Audio and music processing
spatial audio		 0.112010
Binaural Source Localization by Joint Estimation of ILD and ITD · IEEE Trans. Speech Audio Process. 2010

Methods — techniques the papers use, named apart from their topics

parametric modeling · 0.1interaural time difference · 0.1interaural level difference · 0.1
YearPublicationVenuePosition
2010 Spectral similarity metrics for sound source formation based on the common variation cue
Mathieu Lagrange, Martin Raspaud
 Multim. Tools Appl.2
2010 Explicit modeling of temporal dynamics within musical signals for acoustical unit similarity
Mathieu Lagrange, Martin Raspaud, Roland Badeau, Gaël Richard
 Pattern Recognit. Lett.2
2010 Binaural Source Localization by Joint Estimation of ILD and ITD
abstract
In this paper, we propose a binaural source localization method based on interaural time differences (ITDs) and interaural level differences (ILDs). The two cues, computed from a two-channel time-frequency representation, are combined in order to estimate the azimuth of sources in binaural recording. We introduce an individual parametric model for the ITD and ILD, and an average parametric model that sets us free from measurements of the subjects' HRIRs for sound localization. We conduct several experiments to validate the proposed approach and show that it compares favorably with available techniques.
Martin Raspaud, Harald Viste, Gianpaolo Evangelista
 IEEE Trans. Speech Audio Process.1