Sang Bae Chon
Seoul National University
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Publication
Featured researches published by Sang Bae Chon.
IEICE Electronics Express | 2009
Sang Bae Chon; Hee Suk Pang; Mingu Lee; Koeng-Mo Sung
Spectral band replication (SBR) is an effective tool for low bitrate audio codecs such as HE-AAC and enhanced aacPlus. We propose a new algorithm for the bitrate reduction of SBR, which modifies the envelope data coding of SBR considering the threshold in quiet and the masking threshold. Experimental results show that the proposed algorithm significantly reduces the bitrate compared to the conventional SBR with no degradation in perceived sound quality.
IEEE Transactions on Consumer Electronics | 2006
Hwan Shim; Sin-Lyul Lee; Sang Bae Chon; Koeng-Mo Sung
In this paper, a new novel sound field processing system is proposed. This sound field processing system assists listeners in perceiving audible characteristics of a given movie theater or hall, especially with regard to distance and spatial impression. To extend sound space artificially, conventional algorithms reproduce reflected sounds based on the panning law. However, even if this panning law could extend perceived listening space, it accompanies sound coloration, which reduces sound quality. Here, grouped reflections algorithm (GRA) for sound field processing is proposed to reproduce sound fields without sound coloration. Moreover, the algorithm provides higher efficiency, reducing memory requirements of the sound field processing system.
IEICE Electronics Express | 2011
Kuekjae Lee; Sang Bae Chon; Mingu Lee; Koeng-Mo Sung
This paper presents a new method to extract linear-scale perceptual feature as a subsitute of MFCCs for highband (3.4kHz∼) in Speech Bandwidth Extensions(BWE). The feature extraction method is based on the mel-scale constrained Nonnegative Matrix Factorization(NMF), which decompose linear-scale log spectrum into a linear combination of mel-scale latent variables. While MFCCs parametrization contains non-invertible procedures, suggested feature is represented in linear-scale and proper to recover the highband time-domain speech. Experiment results report that suggested feature shows better instrumental performance with narrowband MFCCs than real cepstrum without additional computation.
IEICE Electronics Express | 2010
Mingu Lee; Sang Bae Chon; Jee Ho Park; Koeng-Mo Sung
In this letter, an online segmentation algorithm for audio signal discrimination is presented. By detecting abrupt changes in audio signal features and decimating them followed by strength thresholding, segment boundaries of the audio stream are obtained. The resulting segment boundaries provide efficiency and accuracy for the classification stage of audio signal discrimination system.
IEICE Electronics Express | 2009
Seon-Ho Kim; Sang Bae Chon; Jun-Seok Lim; Koeng-Mo Sung
Least Mean Square (LMS) is an effective adaptive filtering algorithm with advantages of robustness and simplicity. In this paper, we propose two new algorithms, Categorized Variable Step Size LMS (CVSSLMS) and Combined CVSSLMS (CCVSSLMS), based on the categorization of filter status. The step sizes of the proposed algorithms are dynamically updated by optimization for each state. Experiment results show that the proposed algorithms outperform conventional LMS algorithms in both simplicity and robustness.
Journal of The Audio Engineering Society | 2008
Inyong Choi; Barbara G. Shinn-Cunningham; Sang Bae Chon; Koeng-Mo Sung
Journal of The Audio Engineering Society | 2013
Jeong-Hun Seo; Sang Bae Chon; Keong-Mo Sung; Inyong Choi
ICEIC : International Conference on Electronics, Informations and Communications | 2008
Sang Bae Chon; Mingu Lee; In Yong Choi; Koeng-Mo Sung
Audio Engineering Society Conference: 30th International Conference: Intelligent Audio Environments | 2007
In Yong Choi; Sang Bae Chon; Barbara G. Shinn-Cunningham; Koeng-Mo Sung
Audio Engineering Society Conference: 38th International Conference: Sound Quality Evaluation | 2010
Jeong-Hun Seo; Inyong Choi; Sang Bae Chon; Koeng-Mo Sung