75 citations · 95 across the 10 of their papers we have counts for
11 papers
DNN based HRIRs Identification with a Continuously Rotating Speaker Array
Byeong-Yun Ko, Deokki Min, Hyeonuk Nam +1
Conventional static measurement of head-related impulse responses (HRIRs) is time-consuming due to the need for repositioning a speaker array for each azimuth angle. Dynamic approa…
Towards Understanding of Frequency Dependence on Sound Event Detection
Hyeonuk Nam, Seong-Hu Kim, Deokki Min +2
In this work, we conduct an in-depth analysis of two frequency-dependent methods for sound event detection (SED): FilterAugment and frequency dynamic convolution (FDY conv). The go…
Divided spectro-temporal attention for sound event localization and detection in real scenes for DCASE2023 challenge
Yusun Shul, Byeong-Yun Ko, Jung-Woo Choi
Localizing sounds and detecting events in different room environments is a difficult task, mainly due to the wide range of reflections and reverberations. When training neural netw…
Data Augmentation and Squeeze-and-Excitation Network on Multiple Dimension for Sound Event Localization and Detection in Real Scenes
Byeong-Yun Ko, Hyeonuk Nam, Seong-Hu Kim +3
Performance of sound event localization and detection (SELD) in real scenes is limited by small size of SELD dataset, due to difficulty in obtaining sufficient amount of realistic…
Frequency Dependent Sound Event Detection for DCASE 2022 Challenge Task 4
Hyeonuk Nam, Seong-Hu Kim, Deokki Min +3
While many deep learning methods on other domains have been applied to sound event detection (SED), differences between original domains of the methods and SED have not been approp…
HRTF measurement for accurate sound localization cues
Gyeong-Tae Lee, Sang-Min Choi, Byeong-Yun Ko +1
A new database of head-related transfer functions (HRTFs) for accurate sound source localization is presented through precise measurement and post-processing in terms of improved f…
Frequency Dynamic Convolution: Frequency-Adaptive Pattern Recognition for Sound Event Detection
Hyeonuk Nam, Seong-Hu Kim, Byeong-Yun Ko +1
2D convolution is widely used in sound event detection (SED) to recognize two dimensional time-frequency patterns of sound events. However, 2D convolution enforces translation equi…
Heavily Augmented Sound Event Detection utilizing Weak Predictions
Hyeonuk Nam, Byeong-Yun Ko, Gyeong-Tae Lee +4
The performances of Sound Event Detection (SED) systems are greatly limited by the difficulty in generating large strongly labeled dataset. In this work, we used two main approache…
Auxiliary Sequence Labeling Tasks for Disfluency Detection
Dongyub Lee, Byeongil Ko, Myeong Cheol Shin +5
Detecting disfluencies in spontaneous speech is an important preprocessing step in natural language processing and speech recognition applications. Existing works for disfluency de…
Reference and Document Aware Semantic Evaluation Methods for Korean Language Summarization
Dongyub Lee, Myeongcheol Shin, Taesun Whang +5
Text summarization refers to the process that generates a shorter form of text from the source document preserving salient information. Many existing works for text summarization a…
SYSTRAN's Pure Neural Machine Translation Systems
Josep Crego, Jungi Kim, Guillaume Klein +27
Since the first online demonstration of Neural Machine Translation (NMT) by LISA, NMT development has recently moved from laboratory to production systems as demonstrated by severa…