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Lars Hertel

2 accepted papers

2017

CNN-LTE: A class of 1-X pooling convolutional neural networks on label tree embeddings for audio scene classification

ICASSP 2017accepted

We present in this work an approach for audio scene classification. Firstly, given the label set of the scenes, a label tree is automatically constructed where the labels are grouped into meta-classes. This category taxonomy is then used in the feature extraction step in which an audio scene instanc…

Cited by 0SourceScholar
2016

Learning compact structural representations for audio events using regressor banks

ICASSP 2016accepted

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 the input signal. The regressors are class-specific and trained using the random regression forests framework. Given an…

Cited by 0SourceScholar