116 citations · 674 across the 48 of their papers we have counts for
11 papers · 1 filter
Facilitating the Manual Annotation of Sounds When Using Large Taxonomies
Xavier Favory, Eduardo Fonseca, Frederic Font +1
Properly annotated multimedia content is crucial for supporting advances in many Information Retrieval applications. It enables, for instance, the development of automatic tools fo…
Training neural audio classifiers with few data
Jordi Pons, Joan Serrà, Xavier Serra
We investigate supervised learning strategies that improve the training of neural network audio classifiers on small annotated collections. In particular, we study whether (i) a na…
End-to-end music source separation: is it possible in the waveform domain?
Francesc Lluís, Jordi Pons, Xavier Serra
Most of the currently successful source separation techniques use the magnitude spectrogram as input, and are therefore by default omitting part of the signal: the phase. To avoid…
Natural Language Processing for Music Knowledge Discovery
Sergio Oramas, Luis Espinosa-Anke, Francisco Gómez +1
Today, a massive amount of musical knowledge is stored in written form, with testimonies dated as far back as several centuries ago. In this work, we present different Natural Lang…
General-purpose Tagging of Freesound Audio with AudioSet Labels: Task Description, Dataset, and Baseline
Eduardo Fonseca, Manoj Plakal, Frederic Font +4
This paper describes Task 2 of the DCASE 2018 Challenge, titled "General-purpose audio tagging of Freesound content with AudioSet labels". This task was hosted on the Kaggle platfo…
A Simple Fusion of Deep and Shallow Learning for Acoustic Scene Classification
Eduardo Fonseca, Rong Gong, Xavier Serra
In the past, Acoustic Scene Classification systems have been based on hand crafting audio features that are input to a classifier. Nowadays, the common trend is to adopt data drive…