Search Results for author: Archontis Politis

Found 15 papers, 8 papers with code

Position tracking of a varying number of sound sources with sliding permutation invariant training

no code implementations26 Oct 2022 David Diaz-Guerra, Archontis Politis, Tuomas Virtanen

Recent data- and learning-based sound source localization (SSL) methods have shown strong performance in challenging acoustic scenarios.

Association

STARSS22: A dataset of spatial recordings of real scenes with spatiotemporal annotations of sound events

2 code implementations4 Jun 2022 Archontis Politis, Kazuki Shimada, Parthasaarathy Sudarsanam, Sharath Adavanne, Daniel Krause, Yuichiro Koyama, Naoya Takahashi, Shusuke Takahashi, Yuki Mitsufuji, Tuomas Virtanen

Additionally, the report presents the baseline system that accompanies the dataset in the challenge with emphasis on the differences with the baseline of the previous iterations; namely, introduction of the multi-ACCDOA representation to handle multiple simultaneous occurences of events of the same class, and support for additional improved input features for the microphone array format.

Sound Event Localization and Detection

Differentiable Tracking-Based Training of Deep Learning Sound Source Localizers

2 code implementations29 Oct 2021 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.

Classification Direction of Arrival Estimation +1

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

no code implementations26 Jul 2021 Daniel Aleksander Krause, Archontis Politis, Annamaria Mesaros

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.

Mobile Microphone Array Speech Detection and Localization in Diverse Everyday Environments

no code implementations28 Jun 2021 Pasi Pertilä, Emre Cakir, Aapo Hakala, Eemi Fagerlund, Tuomas Virtanen, Archontis Politis, Antti Eronen

Joint sound event localization and detection (SELD) is an integral part of developing context awareness into communication interfaces of mobile robots, smartphones, and home assistants.

Sound Event Localization and Detection

Deep neural network Based Low-latency Speech Separation with Asymmetric analysis-Synthesis Window Pair

no code implementations22 Jun 2021 Shanshan Wang, Gaurav Naithani, Archontis Politis, Tuomas Virtanen

Time-frequency masking or spectrum prediction computed via short symmetric windows are commonly used in low-latency deep neural network (DNN) based source separation.

Deep Clustering Speech Enhancement +1

Overview and Evaluation of Sound Event Localization and Detection in DCASE 2019

3 code implementations6 Sep 2020 Archontis Politis, Annamaria Mesaros, Sharath Adavanne, Toni Heittola, Tuomas Virtanen

A large-scale realistic dataset of spatialized sound events was generated for the challenge, to be used for training of learning-based approaches, and for evaluation of the submissions in an unlabeled subset.

Data Augmentation Sound Event Localization and Detection

A Dataset of Reverberant Spatial Sound Scenes with Moving Sources for Sound Event Localization and Detection

2 code implementations2 Jun 2020 Archontis Politis, Sharath Adavanne, Tuomas Virtanen

This report presents the dataset and the evaluation setup of the Sound Event Localization & Detection (SELD) task for the DCASE 2020 Challenge.

Sound Event Localization and Detection

A multi-room reverberant dataset for sound event localization and detection

3 code implementations21 May 2019 Sharath Adavanne, Archontis Politis, Tuomas Virtanen

This paper presents the sound event localization and detection (SELD) task setup for the DCASE 2019 challenge.

Sound Audio and Speech Processing

Localization, Detection and Tracking of Multiple Moving Sound Sources with a Convolutional Recurrent Neural Network

1 code implementation29 Apr 2019 Sharath Adavanne, Archontis Politis, Tuomas Virtanen

This paper investigates the joint localization, detection, and tracking of sound events using a convolutional recurrent neural network (CRNN).

Sound Event Localization and Detection of Overlapping Sources Using Convolutional Recurrent Neural Networks

7 code implementations30 Jun 2018 Sharath Adavanne, Archontis Politis, Joonas Nikunen, Tuomas Virtanen

In this paper, we propose a convolutional recurrent neural network for joint sound event localization and detection (SELD) of multiple overlapping sound events in three-dimensional (3D) space.

Sound Audio and Speech Processing

Multichannel Sound Event Detection Using 3D Convolutional Neural Networks for Learning Inter-channel Features

no code implementations29 Jan 2018 Sharath Adavanne, Archontis Politis, Tuomas Virtanen

Each of this dataset has a four-channel first-order Ambisonic, binaural, and single-channel versions, on which the performance of SED using the proposed method are compared to study the potential of SED using multichannel audio.

Event Detection Sound Event Detection

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