• Journal of the Institute of Convergence Signal Processing
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• v.10 no.4
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• pp.214-219
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• 2009

This paper proposes a watermarking algorithm considering the frequency characteristics of Haegeum sounds for copyright protection of digital Haegeum sound contents. The harmonics of Haegeum sounds commonly have large magnitude values in 1500Hz~2000Hz and 2800Hz~3500Hz so that those bands are selected to embed a watermark. The proposed method computes the FFT (fast Fourier transform) of the original sound signal and embeds the watermark bits generated by PN (pseudo noise) sequence into the harmonics in the selected bands. Furthermore, the proposed method is robust to lowpass filter, bandpass filter, cropping, noise addition, MP3 compression attacks and the maximum BER (bit error rate) is 1.41% after lowpass filter attack. To measure the quality of the watermarked sound, subjective listening test, MUSHRA (multiple stimuli with hidden reference and anchor), was conducted. The mean value of MUSHRA listening test is bigger than 98 and 96.67 for every Haegeum sounds and Korean classical music with Haeguem, respectively.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.120-126
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• 2007

A principal components analysis of the entire median HRIRs in the CIPIC HRTF database reveals that the individual HRIRs can be adequately reconstructed by a linear combination of several orthonormal basis functions. The basis functions cover the inter-individual and inter-elevation variations in median HRIRs. There are elevation-dependent tendencies in the weights of basis functions, and the basis functions can be ordered according to the magnitude of standard deviation of the weights at each elevation. We propose a HRIR customization method via tuning of the weights of 3 dominant basis functions corresponding to the 3 largest standard deviations at each elevation. Subjective listening test results show that both front-back reversal and vertical perception can be improved with the customized HRIRs.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.7
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• pp.1025-1035
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• 1995

In this paper, we realize a real time digital FM synthesizer based on genetic algorithm using a general purpose digital signal processor. Especially, we synthesize diverse music sounds nicely using a synthesis model consisting of a single modulator and multiple carriers. Also we present genetic algorithm-based technique which determines optimal parameters for reconstruction through FM synthesis of a sound after analyzing the spectrum of PCM data as a standard music sound using FFT. Using the suggested parameter extractiuon algorithm, we extract parameters of several instruments and then synthesize digital FM sounds. To verify the validity of the parameter extraction algorithm as well as realization of a real time digital music synthesizer, the evaluation is first done by listening the sound directly as subjective test. Secondly, to evaluate the synthesized sound objectively with an engineering sense, we compare the synthesized sound with an original one in a time domain and a frequency domain.

• The Journal of the Acoustical Society of Korea
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• v.15 no.1
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• pp.81-86
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• 1996

Some investigations have been made to evaluate the sound quality of a loudspeaker system, objectively and accurately. Also, an algorithm is proposed to predict the various subjective values regarding loudspeaker performance based on the frequency response measured in anechoic chamber. A PC-based software that processes the proposed algorithm has also been developed. To verify the validity of the developed software, three loudspeakers has been evaluated using it and the evaluation results have been compared with the results of the listening test. The comparison between the two showed a good similarity.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.351-352
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• 2006

The objective criterion is necessary to decide the signal for vehicle audio. In this time, the signals have decided by golden ear or some simple parameters. In this paper, we propose the system for sound quality assessment in the vehicle audio signals. The vehicle audio signals were recorded in many vehicles by same condition. From these signals, objective and subjective parameters were extracted and using these signals listening test was done. The function was estimated between three results by simple neural network system. The score of arbitrary signal can be estimated using the function made by three results. In this way, Sound signal quality is assessed objectively.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.137-140
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• 2000

스피커나 앰프 등의 음향기기의 음질을 평가한다는 것은 전기(electric)적인 신호와 음향(acoustic)신호의 종합적인 측정, 분석으로 이루어진다. 또, 이러한 대상에 대한 객관적인 평가 외에 청취자의 심리상태와 관련하여 음질을 분석하는 주관적 음질 평가 역시, 계측기에 의한 측정의 한계와 귀의 탁월한 센싱능력에 힘입어 보편적인 음질 측정법으로 인정받아왔다. 그러나, 주관적 음질 평가법의 경우 개인적 취향이나 음에 대한 숙련정도에 따라 평가가 다를 뿐 아니라 개인의 심리상태에 따라서도 평가가 달라지는 등 그 재현성이나 객관성이 논란이 되어 왔고 이에 대한 연구도 계속되고 있다. 본 연구는 대상으로서의 음향기기(여기서는 스피커)와 청취자의 심리를 포괄하는 시험법인 주관적 음질 평가법에 재현성이나 객관성을 부여하기 위하여 청감에 영향을 미치는 음색인자를 스피커의 특성과 인간의 청각에 근거하여 8가지로 분류하고 이를 평가할 수 있는 Test용 Reference CD를 제작하였다.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.153-156
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• 2003

In this paper, we studied advanced audio/ voice information processing techniques, and trying to introduce more human friendly audio/voice. It is just in the beginning stage. Firstly, we approached in well-known time-domain methods such as moving average, differentiation, interpolation, and decimation. Moreover, some variation of them and envelope contour modification are utilized. We also suggested the MOS test to evaluate subjective listening factors. In the long term viewpoint, user's preference, mood, and environmental conditions will be considered and according to them, we hope our future technique can adapt speech and audio signals automatically.

• Journal of Audiology & Otology
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• v.24 no.4
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• pp.180-190
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• 2020

Background and Objectives: Although many studies have evaluated the effect of the digital noise reduction (DNR) algorithm of hearing aids (HAs) on speech recognition, there are few studies on the effect of DNR on music perception. Therefore, we aimed to evaluate the effect of DNR on music, in addition to speech perception, using objective and subjective measurements. Subjects and Methods: Sixteen HA users participated in this study (58.00±10.44 years; 3 males and 13 females). The objective assessment of speech and music perception was based on the Korean version of the Clinical Assessment of Music Perception test and word and sentence recognition scores. Meanwhile, for the subjective assessment, the quality rating of speech and music as well as self-reported HA benefits were evaluated. Results: There was no improvement conferred with DNR of HAs on the objective assessment tests of speech and music perception. The pitch discrimination at 262 Hz in the DNR-off condition was better than that in the unaided condition (p=0.024); however, the unaided condition and the DNR-on conditions did not differ. In the Korean music background questionnaire, responses regarding ease of communication were better in the DNR-on condition than in the DNR-off condition (p=0.029). Conclusions: Speech and music perception or sound quality did not improve with the activation of DNR. However, DNR positively influenced the listener's subjective listening comfort. The DNR-off condition in HAs may be beneficial for pitch discrimination at some frequencies.

• Korean Journal of Audiology
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• v.24 no.4
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• pp.180-190
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• 2020

Background and Objectives: Although many studies have evaluated the effect of the digital noise reduction (DNR) algorithm of hearing aids (HAs) on speech recognition, there are few studies on the effect of DNR on music perception. Therefore, we aimed to evaluate the effect of DNR on music, in addition to speech perception, using objective and subjective measurements. Subjects and Methods: Sixteen HA users participated in this study (58.00±10.44 years; 3 males and 13 females). The objective assessment of speech and music perception was based on the Korean version of the Clinical Assessment of Music Perception test and word and sentence recognition scores. Meanwhile, for the subjective assessment, the quality rating of speech and music as well as self-reported HA benefits were evaluated. Results: There was no improvement conferred with DNR of HAs on the objective assessment tests of speech and music perception. The pitch discrimination at 262 Hz in the DNR-off condition was better than that in the unaided condition (p=0.024); however, the unaided condition and the DNR-on conditions did not differ. In the Korean music background questionnaire, responses regarding ease of communication were better in the DNR-on condition than in the DNR-off condition (p=0.029). Conclusions: Speech and music perception or sound quality did not improve with the activation of DNR. However, DNR positively influenced the listener's subjective listening comfort. The DNR-off condition in HAs may be beneficial for pitch discrimination at some frequencies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1590-1609
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• 2021

Laughter is one of the most important nonverbal sound that human generates. It is a means for expressing his emotions. The acoustic and contextual features of this specific sound are different from those of speech and many difficulties arise during their modeling process. During this work, we propose an audio laughter generation system based on unsupervised generative models: the autoencoder (AE) and its variants. This procedure is the association of three main sub-process, (1) the analysis which consist of extracting the log magnitude spectrogram from the laughter database, (2) the generative models training, (3) the synthesis stage which incorporate the involvement of an intermediate mechanism: the vocoder. To improve the synthesis quality, we suggest two hybrid models (LSTM-VAE, GRU-VAE and CNN-VAE) that combine the representation learning capacity of variational autoencoder (VAE) with the temporal modelling ability of a long short-term memory RNN (LSTM) and the CNN ability to learn invariant features. To figure out the performance of our proposed audio laughter generation process, objective evaluation (RMSE) and a perceptual audio quality test (listening test) were conducted. According to these evaluation metrics, we can show that the GRU-VAE outperforms the other VAE models.