Hye-Seung Cho

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In this paper, we propose a high-performance audio fingerprinting system used in real-world query-by-example applications for acoustic audio-based content identification, especially for use in heterogeneous portable consumer devices or on-line audio distributed system. In the proposed method, audio fingerprints are generated using a modulated complex lapped(More)
Recently, kernel additive modeling with generalized spatial Wiener filtering (GW) was presented for music/voice separation. In this paper, an adaptive auditory filtering, called generalized weighted β-order MMSE estimation (WbE), is applied to the basic iterative kernel back-fitting algorithm for improving the separation performance of monaural music signal(More)
This paper proposes a robust TV advertisement search based on audio fingerprinting in real environments. To obtain prominent audio peak pairs against different types of distortions, an adaptive thresholding method based on a median filter and peak-picking update is applied. Using the prominent audio peak-pair hashing, the proposed audio fingerprinting(More)
Separating the leading singing voice from the musical background from a monaural recording is a challenging task that appears naturally in several music processing applications. Recently, kernel additive modeling with generalized spatial Wiener filtering (GW) was presented for music/voice separation. In this paper, an adaptive auditory filtering based on(More)
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