23 citations · 91 across the 16 of their papers we have counts for
7 papers · 1 filter
SpecMix : A Mixed Sample Data Augmentation method for Training withTime-Frequency Domain Features
Gwantae Kim, David K. Han, Hanseok Ko
A mixed sample data augmentation strategy is proposed to enhance the performance of models on audio scene classification, sound event classification, and speech enhancement tasks.…
Sinusoidal wave generating network based on adversarial learning and its application: synthesizing frog sounds for data augmentation
Sangwook Park, David K. Han, Hanseok Ko
Simulators that generate observations based on theoretical models can be important tools for development, prediction, and assessment of signal processing algorithms. In order to de…
Analysis Acoustic Features for Acoustic Scene Classification and Score fusion of multi-classification systems applied to DCASE 2016 challenge
Sangwook Park, Seongkyu Mun, Younglo Lee +2
This paper describes an acoustic scene classification method which achieved the 4th ranking result in the IEEE AASP challenge of Detection and Classification of Acoustic Scenes and…
Recursive Whitening Transformation for Speaker Recognition on Language Mismatched Condition
Suwon Shon, Seongkyu Mun, Hanseok Ko
Recently in speaker recognition, performance degradation due to the channel domain mismatched condition has been actively addressed. However, the mismatches arising from language i…
Autoencoder based Domain Adaptation for Speaker Recognition under Insufficient Channel Information
Suwon Shon, Seongkyu Mun, Wooil Kim +1
In real-life conditions, mismatch between development and test domain degrades speaker recognition performance. To solve the issue, many researchers explored domain adaptation appr…
DNN Transfer Learning based Non-linear Feature Extraction for Acoustic Event Classification
Seongkyu Mun, Minkyu Shin, Suwon Shon +3
Recent acoustic event classification research has focused on training suitable filters to represent acoustic events. However, due to limited availability of target event databases…