Sound Event Localization and Detection Using CRNN on Pairs of Microphones

2019/10/22 by Grondin, Francois, Glass, James, Sobieraj, Iwona +1
#Audio and Speech Processing (eess.AS) #FOS: Computer and information sciences #FOS: Electrical engineering #Sound (cs.SD) #electronic engineering #information engineering

paper · doi:10.48550/arxiv.1910.10049

Abstract

This paper proposes sound event localization and detection methods from multichannel recording. The proposed system is based on two Convolutional Recurrent Neural Networks (CRNNs) to perform sound event detection (SED) and time difference of arrival (TDOA) estimation on each pair of microphones in a microphone array. In this paper, the system is evaluated with a four-microphone array, and thus combines the results from six pairs of microphones to provide a final classification and a 3-D direction of arrival (DOA) estimate. Results demonstrate that the proposed approach outperforms the DCASE 2019 baseline system.

Related

• A General Network Architecture for Sound Event Localization and Detection Using Transfer Learning and Recurrent Neural Network
• A two-step system for sound event localization and detection
• Audio Inputs for Active Speaker Detection and Localization via Microphone Array
• Localization, Detection and Tracking of Multiple Moving Sound Sources\n with a Convolutional Recurrent Neural Network
• Sound Event Localization based on Sound Intensity Vector Refined By\n DNN-Based Denoising and Source Separation