• The Journal of the Acoustical Society of Korea
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• v.26 no.2E
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• pp.39-43
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• 2007

Music summarization refers to a technique which automatically extracts the most important and representative segments in music content. In this paper, we propose and evaluate a technique which provides the repeated part in music content as music summary. For extracting a repeated segment in music content, the proposed algorithm uses the weighted sum of similarity measures based on multi-level vector quantization for fixed-length summary or optimal-length summary. For similarity measures, count-based similarity measure and distance-based similarity measure are proposed. The number of the same codeword and the Mahalanobis distance of features which have same codeword at the same position in segments are used for count-based and distance-based similarity measure, respectively. Fixed-length music summary is evaluated by measuring the overlapping ratio between hand-made repeated parts and automatically generated ones. Optimal-length music summary is evaluated by calculating how much automatically generated music summary includes repeated parts of the music content. From experiments we observed that optimal-length summary could capture the repeated parts in music content more effectively in terms of summary length than fixed-length summary.

• The Journal of the Acoustical Society of Korea
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• v.23 no.2E
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• pp.51-55
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• 2004

In this paper, we propose a style-specific language model adaptation scheme using n-gram based tf*idf similarity for Korean spontaneous speech recognition. Korean spontaneous speech shows especially different style-specific characteristics such as filled pauses, word omission, and contraction, which are related to function words and depend on preceding or following words. To reflect these style-specific characteristics and overcome insufficient data for training language model, we estimate in-domain dependent n-gram model by relevance weighting of out-of-domain text data according to their n-. gram based tf*idf similarity, in which in-domain language model include disfluency model. Recognition results show that n-gram based tf*idf similarity weighting effectively reflects style difference.

• The Journal of the Acoustical Society of Korea
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• v.3 no.1
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• pp.16-24
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• 1984

The objective data and subjective data correlated in order to rate sound quality of loudspeaker system and these data were analyzed by the Factor Analysis and Multi-Dimensioinal Scaling. The dimensions yielded Factor Analysis were interpreted as "Contrast", "Metallic", "Rich", "Present" and their relation to physical variables were explored by studying the positions of loudspeaker systems in the respective dimension. When the subjective similarity degree of loudspeaker systems was compared with the objective similarity degree of loudspeaker systems by Multi-Dimensional Scaling, the similarity degree of sound pressure response in the listening room closely coincided with the subjective similarity degree regardless of sound source. This result implies the necessity of measurements taken not only in an anechoic room but also in a listening room in order to rate sound quality of loudspeaker systems.

• The Journal of the Acoustical Society of Korea
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• v.38 no.3
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• pp.314-319
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• 2019

Computing chromagram similarity is indispensable in constructing cover song identification system. This paper proposes a code-based chromagram similarity to reduce the computational and the storage costs for cover song identification. By learning a song-specific codebook, a chromagram sequence is converted into a code sequence, which results in the reduction of the feature storage cost. We build a lookup table over the learned codebooks to compute chromagram similarity efficiently. Experiments on two music datasets were performed to compare the proposed code-based similarity with the conventional one in terms of cover song search accuracy, feature storage, and computational cost.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.200-206
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• 2024

Computing music similarity is an indispensable component in developing music search service. This paper proposes a relevance weight of each chromagram vector for cover song identification in computing a music similarity function in order to boost identification accuracy. We derive a music similarity function using the relevance weight based on the probabilistic relevance model, where higher relevance weights are assigned to less frequently-occurring discriminant chromagram vectors while lower weights to more frequently-occurring ones. Experimental results performed on two cover music datasets show that the proposed music similarity improves the cover song identification performance.

• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.136-141
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• 2011

In this paper, a method for measuring rhythmic similarity between two sound signals for auditory memory game is proposed. The proposed method analyzes energy fluctuation, the temporal duration of energy peak, the timbre of two signals, and detects beat positions for each signal. Then, it determines the rhythm vector after compensating a difference in tempo and the number of beats between two signals. Finally, a method for rhythmic similarity measurement is defined as a function of the dissimilarity between two rhythm vectors and a difference in the number of beats. The rhythmic similarity measured by the proposed method and that by the subjective listening test are compared, and the correlation of 0.86 between two results is achieved.

• The Journal of the Acoustical Society of Korea
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• v.27 no.2E
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• pp.51-56
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• 2008

In this paper, we propose an effective method for music summarization which automatically extracts a representative part of the music by using signal processing technology. Proposed method uses a vector quantization technique to extract several segments which can be regarded as the most important contents in the music. In general, there is a repetitive pattern in music, and human usually recognizes the most important or catchy tune from the repetitive pattern. Thus the repetition which is extracted using segment similarity is considered to express a music summary. The segments extracted are again combined to generate a complete music summary. Experiments show the proposed method captures the main theme of the music more effectively than conventional methods. The experimental results also show that the proposed method could be used for real-time application since the processing time in generating music summary is much faster than other methods.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.2
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• pp.275-281
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• 2010

In this paper, a geometric similarity law is introduced to the performance test of a large-sized silencer used in ship engine or plant system. A test of scale-down model enable to yield the cost and time saving in developing large-sized silencer considerably. Two types of silencer, resonator and expansion chamber, were analyzed by a theoretical method and an acoustical FEM(finite element method) in order to obtain geometric similarity variables. A method is proposed to estimate the transmission loss of prototype model using the test results of scale-down model. Two actual large-sized silencer, which consist of resonator and expansion chamber, were analysed by an acoustical FE analysis. Consequently, the proposed method predicts effectively the performance of prototype silencers using those of scale-down models.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1995.04a
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• pp.196-201
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• 1995

The broadband and discrete sources of sound in small cooling fans of propeller type and centrifugal type were investigated to understand the turbulent vortex structures from many bladed fans using ANSI test plenum for small air-moving devices (AMDs). The noise measurement method uses the plenum as a test apparatus to determine the acoustic source spectral density function at each operating conditions similar to real engineering applications based on acoustic similarity laws. The characteristics of fans including the head rise vs. volumetric flow rate performance were measured using a performance test facility. The sound power spectrum is decomposed into two non-dimensional functions: an acoustic source spectral distribution function F(St,.phi.) and an acoustic system response function G(He,.phi.) where St, He, and .phi. are the Strouhal number, the Helmholtz number, and the volumetric flow rate coefficient, respectively. The autospectra of radiated noise measurements for the fan operating at several volumetric flow rates,.phi., are analyzed using acoustical similarity. The rotating stall in the small propeller fan with a bell-mouth guided is mainly due to a leading edge separation. It creates a blockage in the passage and the reduction in the flow rate. The sound power levels with respect to the rotational speeds were measured to reveal the mechanisms of stall and/or surge for different loading conditions and geometries, for example, fans installed with a impinging plate. Lee and Meecham (1993) studied the effect of the large-scale motions like impinging normally on a flat plate using Large-Eddy Simulation(LES) and Lighthill's analogy.[ASME Winter Annual Meeting 1993, 93-WA/NCA-22]. The dipole and quadrupole sources in the fans tested are shown closely related to the vortex structures involved using cross-correlations of the hot-wire and microphone signals.

• The Journal of the Acoustical Society of Korea
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• v.41 no.6
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• pp.662-667
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• 2022

Computing music similarity is an indispensable component in developing music search service. This paper focuses on learning a music similarity function in order to boost cover song identification performance. By using the probabilistic linear discriminant analysis, we construct a latent music space where the distances between cover song pairs reduces while the distances between the non-cover song pairs increases. We derive a music similarity function by testing hypothesis, whether two songs share the same latent variable or not, using the probabilistic models with the assumption that observed music features are generated from the learned latent music space. Experimental results performed on two cover music datasets show that the proposed music similarity improves the cover song identification performance.