43 citations · 74 across the 11 of their papers we have counts for
13 papers
Differentiable Tracking-Based Training of Deep Learning Sound Source Localizers
Sharath Adavanne, Archontis Politis, Tuomas Virtanen
Data-based and learning-based sound source localization (SSL) has shown promising results in challenging conditions, and is commonly set as a classification or a regression problem…
Joint Direction and Proximity Classification of Overlapping Sound Events from Binaural Audio
Daniel Aleksander Krause, Archontis Politis, Annamaria Mesaros
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…
A Dataset of Dynamic Reverberant Sound Scenes with Directional Interferers for Sound Event Localization and Detection
Archontis Politis, Sharath Adavanne, Daniel Krause +3
This report presents the dataset and baseline of Task 3 of the DCASE2021 Challenge on Sound Event Localization and Detection (SELD). The dataset is based on emulation of real recor…
Assessment of Self-Attention on Learned Features For Sound Event Localization and Detection
Parthasaarathy Sudarsanam, Archontis Politis, Konstantinos Drossos
Joint sound event localization and detection (SELD) is an emerging audio signal processing task adding spatial dimensions to acoustic scene analysis and sound event detection. A po…
Mobile Microphone Array Speech Detection and Localization in Diverse Everyday Environments
Pasi Pertilä, Emre Cakir, Aapo Hakala +4
Joint sound event localization and detection (SELD) is an integral part of developing context awareness into communication interfaces of mobile robots, smartphones, and home assist…
Deep neural network Based Low-latency Speech Separation with Asymmetric analysis-Synthesis Window Pair
Shanshan Wang, Gaurav Naithani, Archontis Politis +1
Time-frequency masking or spectrum prediction computed via short symmetric windows are commonly used in low-latency deep neural network (DNN) based source separation. In this paper…