mlsanityData to 14 Oct 2026

CoLoC: Conditioned Localizer and Classifier for Sound Event Localization and Detection

arXiv 2210.13932 ↗First posted 25 Oct 2022cs.SD cs.LG eess.AScited by 0

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Abstract (arXiv)

In this article, we describe Conditioned Localizer and Classifier (CoLoC) which is a novel solution for Sound Event Localization and Detection (SELD). The solution constitutes of two stages: the localization is done first and is followed by classification conditioned by the output of the localizer. In order to resolve the problem of the unknown number of sources we incorporate the idea borrowed from Sequential Set Generation (SSG). Models from both stages are SELDnet-like CRNNs, but with single outputs. Conducted reasoning shows that such two single-output models are fit for SELD task. We show that our solution improves on the baseline system in most metrics on the STARSS22 Dataset.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 13 references that are in the map. First posted on arXiv 25 Oct 2022.

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9 of 13 references.

References · 9

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2017Deep Setscited by 1,421
  3. 2020FSD50K: An Open Dataset of Human-Labeled Sound Eventscited by 342
  4. 2018Sound Event Localization and Detection of Overlapping Sources Using Convolutional Recurrent Neural Networkscited by 85
  5. 2020ACCDOA: Activity-Coupled Cartesian Direction of Arrival Representation for Sound Event Localization and Detectioncited by 26
  6. 2020An Improved Event-Independent Network for Polyphonic Sound Event Localization and Detectioncited by 25
  7. 2021Multi-ACCDOA: Localizing and Detecting Overlapping Sounds from the Same Class with Auxiliary Duplicating Permutation Invariant Trainingcited by 25
  8. 2022STARSS22: A dataset of spatial recordings of real scenes with spatiotemporal annotations of sound eventscited by 16
  9. 2019Sound source detection, localization and classification using consecutive ensemble of CRNN modelscited by 8

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