124 citations · 382 across the 13 of their papers we have counts for
7 papers · 1 filter
CaR-FOREST: Joint Classification-Regression Decision Forests for Overlapping Audio Event Detection
Huy Phan, Lars Hertel, Marco Maass +2
This report describes our submissions to Task2 and Task3 of the DCASE 2016 challenge. The systems aim at dealing with the detection of overlapping audio events in continuous stream…
CNN-LTE: a Class of 1-X Pooling Convolutional Neural Networks on Label Tree Embeddings for Audio Scene Recognition
Huy Phan, Lars Hertel, Marco Maass +2
We describe in this report our audio scene recognition system submitted to the DCASE 2016 challenge. Firstly, given the label set of the scenes, a label tree is automatically const…
Label Tree Embeddings for Acoustic Scene Classification
Huy Phan, Lars Hertel, Marco Maass +2
We present in this paper an efficient approach for acoustic scene classification by exploring the structure of class labels. Given a set of class labels, a category taxonomy is aut…
Classifying Variable-Length Audio Files with All-Convolutional Networks and Masked Global Pooling
Lars Hertel, Huy Phan, Alfred Mertins
We trained a deep all-convolutional neural network with masked global pooling to perform single-label classification for acoustic scene classification and multi-label classificatio…
Learning Compact Structural Representations for Audio Events Using Regressor Banks
Huy Phan, Marco Maass, Lars Hertel +3
We introduce a new learned descriptor for audio signals which is efficient for event representation. The entries of the descriptor are produced by evaluating a set of regressors on…
Robust Audio Event Recognition with 1-Max Pooling Convolutional Neural Networks
Huy Phan, Lars Hertel, Marco Maass +1
We present in this paper a simple, yet efficient convolutional neural network (CNN) architecture for robust audio event recognition. Opposing to deep CNN architectures with multipl…