Co-Localization of Audio Sources in Images Using Binaural Features and Locally-Linear Regression

Antoine Deleforge, Radu Horaud, Yoav Y. Schechner, Laurent Girin

Research output: Contribution to journalArticlepeer-review


This paper addresses the problem of localizing audio sources using binaural measurements. We propose a supervised formulation that simultaneously localizes multiple sources at different locations. The approach is intrinsically efficient because, contrary to prior work, it relies neither on source separation, nor on monaural segregation. The method starts with a training stage that establishes a locally linear Gaussian regression model between the directional coordinates of all the sources and the auditory features extracted from binaural measurements. While fixed-length wide-spectrum sounds (white noise) are used for training to reliably estimate the model parameters, we show that the testing (localization) can be extended to variable-length sparse-spectrum sounds (such as speech), thus enabling a wide range of realistic applications. Indeed, we demonstrate that the method can be used for audio-visual fusion, namely to map speech signals onto images and hence to spatially align the audio and visual modalities, thus enabling to discriminate between speaking and non-speaking faces. We release a novel corpus of real-room recordings that allow quantitative evaluation of the co-localization method in the presence of one or two sound sources. Experiments demonstrate increased accuracy and speed relative to several state-of-the-art methods.

Original languageEnglish
Article number7045516
Pages (from-to)718-731
Number of pages14
JournalIEEE Transactions on Audio, Speech and Language Processing
Issue number4
StatePublished - Apr 2015


  • Audio-visual fusion
  • binaural hearing
  • mixture model
  • regression
  • sound-source localization
  • supervised learning

All Science Journal Classification (ASJC) codes

  • Acoustics and Ultrasonics
  • Electrical and Electronic Engineering


Dive into the research topics of 'Co-Localization of Audio Sources in Images Using Binaural Features and Locally-Linear Regression'. Together they form a unique fingerprint.

Cite this