Joint Direction and Proximity Classification of Overlapping Sound Events from Binaural Audio

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

4 Citations (Scopus)
12 Downloads (Pure)


Sound source proximity and distance estimation are of great interest in many practical applications, since they provide significant information for acoustic scene analysis. As both tasks share complementary qualities, ensuring efficient interaction between these two is crucial for a complete picture of an aural environment. In this paper, we aim to investigate several ways of performing joint proximity and direction estimation from binaural recordings, both defined as coarse classification problems based on Deep Neural Networks (DNNs). Considering the limitations of binaural audio, we propose two methods of splitting the sphere into angular areas in order to obtain a set of directional classes. For each method we study different model types to acquire information about the direction-of-arrival (DoA). Finally, we propose various ways of combining the proximity and direction estimation problems into a joint task providing temporal information about the onsets and offsets of the appearing sources. Experiments are performed for a synthetic reverberant binaural dataset consisting of up to two overlapping sound events.
Original languageEnglish
Title of host publication2021 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)
Number of pages5
ISBN (Electronic)978-1-7281-5871-6
Publication statusPublished - 2020
Publication typeA4 Article in conference proceedings
EventIEEE International Conference on Human-Machine Systems - Virtual, Rome, Italy
Duration: 7 Sept 20209 Sept 2020


ConferenceIEEE International Conference on Human-Machine Systems
CityVirtual, Rome


  • Deep learning
  • Image analysis
  • Direction-of-arrival estimation
  • Conferences
  • Estimation
  • Signal processing
  • Multitasking
  • binaural audio
  • binaural localization
  • distance estimation

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  • Publication forum level 1


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