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David K. Han

5 accepted papers

2021

Self-Training for Sound Event Detection in Audio Mixtures

ICASSP 2021accepted

Sound event detection (SED) takes on the task of identifying presence of specific sound events in a complex audio recording. SED has tremendous implications in video analytics, smart speaker algorithms and audio tagging. Recent advances in deep learning have afforded remarkable advances in performan…

Cited by 0SourceScholar
2020

CAFE-GAN: Arbitrary Face Attribute Editing with Complementary Attention Feature

ECCV 2020poster

The goal of face attribute editing is altering a facial image according to given target attributes such as hair color, mustache, gender, etc. It belongs to the image-to-image domain transfer problem with a set of attributes considered as a distinctive domain. There have been some works in multi-doma…

Cited by 38SourcePDFScholar
2017

Deep Neural Network based learning and transferring mid-level audio features for acoustic scene classification

ICASSP 2017accepted

Deep Neural Network (DNN) based transfer learning has been shown to be effective in Visual Object Classification (VOC) for complementing the deficit of target domain training samples by adapting classifiers that have been pre-trained for other large-scaled DataBase (DB). Although there exists an abu…

Cited by 0SourceScholar
2017

Subspace projection cepstral coefficients for noise robust acoustic event recognition

ICASSP 2017accepted

In this paper, a novel feature for noise robust sound event recognition is proposed. The proposed feature is obtained by a two-step procedure. First, a subspace bank is established via target event analysis in complex vector space. Then, by projecting observation vectors onto the subspace bank, nois…

Cited by 0SourceScholar