33 citations · 82 across the 8 of their papers we have counts for
7 papers · 1 filter
What Makes Audio Event Detection Harder than Classification?
Huy Phan, Philipp Koch, Fabrice Katzberg +4
There is a common observation that audio event classification is easier to deal with than detection. So far, this observation has been accepted as a fact and we lack of a careful a…
Measurement of Sound Fields Using Moving Microphones
Fabrice Katzberg, Radoslaw Mazur, Marco Maass +2
The sampling of sound fields involves the measurement of spatially dependent room impulse responses, where the Nyquist-Shannon sampling theorem applies in both the temporal and spa…
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…
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…