• Journal of information and communication convergence engineering
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• v.18 no.2
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• pp.115-122
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• 2020

Audiovisual (AV) facilities such as TVs and signage are installed in various public places. However, audio cannot be used to prevent noise and interference from individuals, which results in a loss of concentration and understanding of AV content. To address this problem, a total technique for remotely listening to audio from audiovisual facilities with clean sound quality while maintaining video and lip-syncing through personal smart mobile devices is proposed in this paper. Through the experimental results, the proposed scheme has been verified to reduce system power consumption by 8% to 16% and provide real-time processing with a low latency of 120 ms. The system described in this paper will contribute to the activation of audio telehearing services as it is possible to provide audio remote services in various places, such as express buses, trains, wide-area and intercity buses, public waiting rooms, and various application services.

• The Journal of the Acoustical Society of Korea
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• v.23 no.3E
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• pp.91-97
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• 2004

In this paper, we propose a classification system of TV program scenes based on audio information. The system classifies the video scene into six categories of commercials, basketball games, football games, news reports, weather forecasts and music videos. Two type of audio feature set are extracted from each audio frame-timbral features and coefficient domain features which result in 58-dimensional feature vector. In order to reduce the computational complexity of the system, 58-dimensional feature set is further optimized to yield l0-dimensional features through Sequential Forward Selection (SFS) method. This down-sized feature set is finally used to train and classify the given TV program scenes using κ -NN, Gaussian pattern matching algorithm. The classification result of 91.6% reported here shows the promising performance of the video scene classification based on the audio information. Finally, the system stability problem corresponding to different query length is investigated.

• ETRI Journal
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• v.28 no.2
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• pp.219-222
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• 2006

Virtual source location information (VSLI) has been newly utilized as a spatial cue for compact representation of multichannel audio. This information is represented as the azimuth of the virtual source vector. The superiority of VSLI is confirmed by comparison of the spectral distances, average bit rates, and subjective assessment with a conventional cue.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.5 no.1
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• pp.37-42
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• 2006

A reversible audio watermarking algorithm is presented in this paper. This algorithm transforms the audio signal with the integer wavelet transform first in order to enhance the correlation between neighbor audio samples. Audio signal has low correlation between neighbor samples, which makes it difficult to apply difference expansion scheme. Second, a novel difference expansion scheme is used to embed more data by reducing the size of location map. Therefore, the difference expansion scheme used in this paper theoretically secures high embedding capacity under low perceptual distortion. Experiments show that this scheme can hide large number of information bits and keeps high perceptual quality.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.768-771
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• 2004

In this paper, we propose a content-based audio genre classification algorithm that automatically classifies the query audio into five genres such as Classic, Hiphop, Jazz, Rock, Speech using digital signal processing approach. From the 20 second query audio file, 54 dimensional feature vectors, including Spectral Centroid, Rolloff, Flux, LPC, MFCC, is extracted from each query audio. For the classification algorithm, k-NN, Gaussian, GMM classifier is used. In order to choose optimum features from the 54 dimension feature vectors, SFS (Sequential Forward Selection) method is applied to draw 10 dimension optimum features and these are used for the genre classification algorithm. From the experimental result, we verify the superior performance of the SFS method that provides near $90{\%}$ success rate for the genre classification which means $10{\%}$-$20{\%}$ improvements over the previous methods

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.49-52
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• 2008

This paper briefly introduces the current status of MPEG Audio Subgroup activities for standardizing a new audio coding technologies. Currently MPEG Audio Subgroup focused on spatial audio coding tools for compressing multiple audio objects and unified coding tools for presenting the consistence performance on speech and audio signal at the same time. Also a new MAF (MPEG Application Format) for interactive music was introduced at the 84th MPEG meeting.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.224-231
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• 2013

Defining the concept of prominent audio content as the most informative audio content from the users' perspective within a given unstructured audio segment, we propose a simple but robust intensity-based attack/release pattern features to detect the prominent audio content. We also propose a web-based annotation procedure to retrieve users' subjective perception and annotated 18 hours of video clips across various genres, such as cartoon, movie, news, etc. The experiments with a linear classification method whose models are trained for speech, music, and sound effect demonstrate promising - but varying across the genres of programs - results (e.g., 86.7% weighted accuracy for speech-oriented talk shows and 49.3% weighted accuracy for {action movies}).

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.353-362
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• 2005

Recently, study of Bimodal recognition has become very active. In this paper we propose a Bimodal user recognition system that uses face information and audio information. Face recognition consists of face detection step and face recognition step. Face detection uses AdaBoost to find face candidate area. After finding face candidates, PCA feature extraction is applied to decrease the dimension of feature vector. And then, SVM classifiers are used to detect and recognize face. Audio recognition uses MFCC for audio feature extraction and HMM is used for audio recognition. Experimental results show that the Bimodal recognition can improve the user recognition rate much more than audio only recognition, especially in the Presence of noise.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2165-2170
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• 2008

In this parer, it is implemented a Local distribution Audio System, based on AoIP(Audio over Internet Protocol) of a part of TCP/IP Network which belongs to Internet transmission technology. The system is controlled based on SNMP(Simple Network Management Protocol) and it is transferred to UDP as packet after changing from Analog audio sources to Digital audio sources. The implemented Local distribution Audio System have presented practical possibilities in PA system transmitting various audio sources to several areas, dispersedly and using multichannel audio like Home theaters in the limelight, recently.

• The Journal of the Acoustical Society of Korea
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• v.27 no.5
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• pp.244-251
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• 2008

In this research, we propose an unsupervised debate indexing method using audio and visual information. The proposed method combines clustering results of speech by BIC and visual by distance function. The combination of audio-visual information reduces the problem of individual use of speech and visual information. Also, an effective content based analysis is possible. We have performed various experiments to evaluate the proposed method according to use of audio-visual information for five types of debate data. From experimental results, we found that the effect of audio-visual integration outperforms individual use of speech and visual information for debate indexing.