DCASE 2019 challenge submission reports >85% accuracy on acoustic scene classification via GAN augmentation fused with 1D and 2D CNN classifiers.
Deep Scattering Spectrum
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abstract
A scattering transform defines a locally translation invariant representation which is stable to time-warping deformations. It extends MFCC representations by computing modulation spectrum coefficients of multiple orders, through cascades of wavelet convolutions and modulus operators. Second-order scattering coefficients characterize transient phenomena such as attacks and amplitude modulation. A frequency transposition invariant representation is obtained by applying a scattering transform along log-frequency. State-the-of-art classification results are obtained for musical genre and phone classification on GTZAN and TIMIT databases, respectively.
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Integrating the Data Augmentation Scheme with Various Classifiers for Acoustic Scene Modeling
DCASE 2019 challenge submission reports >85% accuracy on acoustic scene classification via GAN augmentation fused with 1D and 2D CNN classifiers.