• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.20-22
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• 2014

선박, 해양플랜트에 적용되는 PAGA System 는 선내 모든 선원 및 승객에 대하여 정보전달 기능뿐 아니라 위급 상황 발생시 신속한 상황 전달 및 대피를 위한 안전상의 이유로서 매우 중요시 되고 있다. PAGA 의 핵심이 되는 Audio Coverage 의 경우, 초기 설계단계에서 해석을 통해 스피커 배치가 이루어지는데, 본 논문에서는 이러한 PAGA Audio Coverage 관련 요구조건과 합리적인 적용방안, 해석 및 평가 방안에 대하여 사례를 통해 소개하고자 한다.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.557-560
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• 2004

본 논문에서는 실내음향을 측정하기 위해 사용되는 음향 측정 신호인 blank pistol, maximum length sequence, sine sweep 을 이용한 충격응답 특성을 분석한다. 각 충격응답의 실내음향 인자들을 먼저 비교 분석하고 sine sweep 속도에 따른 충격응답 특성을 분석하여 최적의 실내음향 인자를 찾기 위한 sine sweep 속도를 결정한다.

• The Journal of the Acoustical Society of Korea
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• v.28 no.7
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• pp.674-679
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• 2009

This paper proposes a method of player event retrieval using combination of two functions: detection of player name in speech information and detection of sound event from audio information in golf videos. The system consists of indexing module and retrieval module. At the indexing time audio segmentation and noise reduction are applied to audio stream demultiplexed from the golf videos. The noise-reduced speech is then fed into speech recognizer, which outputs spoken descriptors. The player name and sound event are indexed by the spoken descriptors. At search time, text query is converted into phoneme sequences. The lists of each query term are retrieved through a description matcher to identify full and partial phrase hits. For the retrieval of the player name, this paper compares the results of word-based, phoneme-based, and hybrid approach.

• The Journal of the Acoustical Society of Korea
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• v.19 no.4
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• pp.58-68
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• 2000

This paper proposes a sinusoidal modeling of polyphonic audio signals. Sinusoidal modeling which has been applied well to speech and monophonic signals cannot be applied directly to polyphonic signals because a window size for sinusoidal analysis cannot be determined over the entire signal. In addition, for high quality synthesized signal transient parts like attacks should be preserved which determines timbre of musical instrument. In this paper, a multiresolution filter bank is designed which splits the input signal into six octave-spaced subbands without aliasing and sinusoidal modeling is applied to each subband signal. To alleviate smearing of transients in sinusoidal modeling a dynamic segmentation method is applied to subbands which determines the analysis-synthesis frame size adaptively to fit time-frequency characteristics of the subband signal. The improved dynamic segmentation is proposed which shows better performance about transients and reduced computation. For various polyphonic audio signals the result of simulation shows the suggested sinusoidal modeling can model polyphonic audio signals without loss of perceptual quality.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.819-825
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• 2014

In this paper, monaural ambient component extraction algorithm based on nonnegative matrix factorization (NMF) is described. The ambience component extraction algorithm in this paper is developed for audio upmixing system; Recent researches have shown that they can enhance listener envelopment if the extracted ambient signal is applied into the multichannel audio upmixing system. However, the conventional method stores all of the audio signal and processes all at once, so it cannot be applied to streaming system and digital signal processor (DSP) system. In this paper, the ambient component extraction algorithm based on on-line nonnegative matrix factorization is developed and evaluated to solve the problem. As a result of analysis of the processed signal with spectral flatness measures in the experiment, it was shown that the developed system can extract the ambient signal similarly with the conventional batch process system.

• Journal of Broadcast Engineering
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• v.21 no.6
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• pp.977-985
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• 2016

In this paper, we propose a new method for on-line genre classification using spectrogram and deep neural network. For on-line processing, the proposed method inputs an audio signal for a time period of 1sec and classifies its genre among 3 genres of speech, music, and effect. In order to provide the generality of processing, it uses the spectrogram as a feature vector, instead of MFCC which has been widely used for audio analysis. We measure the performance of genre classification using real TV audio signals, and confirm that the proposed method has better performance than the conventional method for all genres. In particular, it decreases the rate of classification error between music and effect, which often occurs in the conventional method.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.94-104
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• 2022

As the audio content market grows due to the spread of the AI speaker market and the influence of connected cars, the demand for podcast service is increasing. Therefore, in this study, the behaviors of podcast users were identified and the user types were classified. In the background study, podcast usage motives and user types were studied, and they were referred to when making the questionnaire. In the survey, preferred audio content was identified according to the situation, and in the in-depth interview, the user type and insights were derived by identifying the audio service usage behavior. As a result of the survey, there was little difference between preferred content for single listening and multitasking, but the difference in preferred content according to time period was statistically significant. The three user types derived from the in-depth interview were divided into users who listen alone for the purpose of study, find and listen to useful information quickly while on the go, and multitask and listen to the light and comfortable contents. It is expected that the results of this study will be an important reference for designing an audio content platform to improve user experience.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.76-83
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• 2006

A main objective of audio equalizer is for user to tailor acoustic frequency response to increase sound comfort and example applications of audio equalizer includes large-scale audio system to portable audio such as mobile MP3 player. Up to now, all the audio equalizer requires manual setting to equalize frequency bands to create suitable sound quality for each genre of music. In this paper, we propose an intelligent audio graphic equalizer system that automatically classifies the music genre using music content analysis and then the music sound is boosted with the given frequency gains according to the classified musical genre when playback. In order to reproduce comfort sound, the musical genre is determined based on two-step hierarchical algorithm - coarse-level and fine-level classification. It can prevent annoying sound reproduction due to the sudden change of the equalizer gains at the beginning of the music playback. Each stage of the music classification experiments shows at least 80% of success with complete genre classification and equalizer operation within 2 sec. Simple S/W graphical user interface of 3-band automatic equalizer is implemented using visual C on personal computer.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.169-179
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• 2016

Recently, MPEG-H has been standardizing for a multimedia coder in UHDTV (Ultra-High-Definition TV). Thus, the demand for not only channel-based audio contents but also object-based audio contents is more increasing, which results in developing a new technique of converting channel-based audio contents to object-based ones. In this paper, a non-uniform linear microphone array based source separation method is proposed for realizing such conversion. The proposed method first analyzes the arrival time differences of input audio sources to each of the microphones, and the spectral magnitudes of each sound source are estimated at the horizontal directions based on the analyzed time differences. In order to demonstrate the effectiveness of the proposed method, objective performance measures of the proposed method are compared with those of conventional methods such as an MVDR (Minimum Variance Distortionless Response) beamformer and an ICA (Independent Component Analysis) method. As a result, it is shown that the proposed separation method has better separation performance than the conventional separation methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.5
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• pp.895-907
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• 2020

With the recent increasing influence of multimedia content other than the text-based content, services that help to process information in content brings us great convenience. These services' representative features are searching and masking the sensitive data. It is not difficult to find the solutions that provide searching and masking function for text information and image. However, even though we recognize the necessity of the technology for searching and masking a part of the audio data, it is not easy to find the solution because of the difficulty of the technology. In this study, we propose web application that provides searching and masking functions for audio data using audio partitioning method. While we are achieving the research goal, we evaluated several speech to text conversion APIs to choose a proper API for our purpose and developed regular expressions for searching sensitive information. Lastly we evaluated the accuracy of the developed searching and masking feature. The contribution of this work is in design and implementation of searching and masking a sensitive information from the audio data by the various functionality proving experiments.