activity
20192026
most citedAcoustic Scene Classification with Squeeze-Excitation Residual Networks

40 citations · 87 across the 18 of their papers we have counts for

collaborators
Showing 2020Show all

5 papers · 1 filter

eess.AS2020★ 6 cited

Listen carefully and tell: an audio captioning system based on residual learning and gammatone audio representation

Sergi Perez-Castanos, Javier Naranjo-Alcazar, Pedro Zuccarello +1

Automated audio captioning is machine listening task whose goal is to describe an audio using free text. An automated audio captioning system has to be implemented as it accepts an…

eess.AS2020★ 5 cited

Anomalous Sound Detection using unsupervised and semi-supervised autoencoders and gammatone audio representation

Sergi Perez-Castanos, Javier Naranjo-Alcazar, Pedro Zuccarello +1

Anomalous sound detection (ASD) is, nowadays, one of the topical subjects in machine listening discipline. Unsupervised detection is attracting a lot of interest due to its immedia…

cs.SD2020★ 2 cited

Sound Event Localization and Detection using Squeeze-Excitation Residual CNNs

Javier Naranjo-Alcazar, Sergi Perez-Castanos, Jose Ferrandis +2

Sound Event Localization and Detection (SELD) is a problem related to the field of machine listening whose objective is to recognize individual sound events, detect their temporal…

cs.SD2020★ 40 cited

Acoustic Scene Classification with Squeeze-Excitation Residual Networks

Javier Naranjo-Alcazar, Sergi Perez-Castanos, Pedro Zuccarello +1

Acoustic scene classification (ASC) is a problem related to the field of machine listening whose objective is to classify/tag an audio clip in a predefined label describing a scene…

cs.SD2020★ 1 cited

An Open-set Recognition and Few-Shot Learning Dataset for Audio Event Classification in Domestic Environments

Javier Naranjo-Alcazar, Sergi Perez-Castanos, Pedro Zuccarrello +4

The problem of training with a small set of positive samples is known as few-shot learning (FSL). It is widely known that traditional deep learning (DL) algorithms usually show ver…