• Journal of Broadcast Engineering
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• v.24 no.7
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• pp.1228-1236
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• 2019

Recently, media platforms such as YouTube and Twitch provide services that can generate personal revenue by utilizing media content produced by individuals. In this regard, interest in the copyright of media content is increasing. In particular, in the case of an audio source, competition for securing audio source copyright is fierce because it is an essential element for almost all media content production. In this paper, we propose a method to store the audio source and its signature using a blockchain and distributed storage system to verify the copyright of music content. To identify the possibility of extracting the audio signature of the audio source and to include it as blockchain transaction data, we implement the audio source and its signature file upload system based on the proposed scheme. In addition, we show the effectiveness of the proposed method through experiments on uploading and retrieving audio files and identify future improvements.

• The Journal of the Acoustical Society of Korea
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• v.26 no.3E
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• pp.74-79
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• 2007

In this paper, we report our recent work on a indexing and retrieval system of broadcast news using audio content analysis. Key issues addressed in this work are two major parts of the audio indexing system: anchorperson detection based on audio segmentation, and phone-based spoken document retrieval, developed in the framework of the emerging MPEG-7 standard. Experiments are conducted on a database of Britisch broadcast news videos. We discuss the development of the retrieval system, and the evaluation of each part and the retrieval system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.461-468
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• 2000

Amounts of audio data used in several computer application have necessitated the development of audio database systems with newer features such as content-based queries and similarity searches to manage and use such data. Fast and accurate retrievals for content-based queries are crucial for such systems to be useful. Efficient content-based indexing and similarity searching schemes are keys to providing fast and relevant data retrievals. This paper present a method for indexing of Korean Traditional Music audio data based on wavelets. Also this paper present possibility of wavelet based audio indexing.

• 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 Digital Contents Society
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• v.18 no.5
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• pp.811-820
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• 2017

For content-based audio retrieval which is one of main functions in audio service, the techniques for extracting fingerprints from the audio source, storing and indexing them in a database are widely used. However, if the fingerprints of new audio sources are continually inserted into the database, there is a problem that space efficiency as well as audio retrieval performance are gradually deteriorated. Therefore, there is a need for techniques to support efficient expansion of audio database without periodic reorganization of the database that would increase the system operation cost. In this paper, we design a content-based audio retrieval system that solves this problem by using MapReduce and NoSQL database in a cluster computing environment based on the Shazam's fingerprinting algorithm, and evaluate its performance through a detailed set of experiments using real world audio data.

• ETRI Journal
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• v.24 no.3
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• pp.181-189
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• 2002

Digital watermark technology is now drawing attention as a new method of protecting digital content from unauthorized copying. This paper presents a novel audio watermarking algorithm to protect against unauthorized copying of digital audio. The proposed watermarking scheme includes a psychoacoustic model of MPEG audio coding to ensure that the watermarking does not affect the quality of the original sound. After embedding the watermark, our scheme extracts copyright information without access to the original signal by using a whitening procedure for linear prediction filtering before correlation. Experimental results show that our watermarking scheme is robust against common signal processing attacks and it introduces no audible distortion after watermark insertion.

• ETRI Journal
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• v.36 no.6
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• pp.999-1007
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• 2014

The robustness of an audio fingerprinting system in an actual noisy environment is a major challenge for audio-based content identification. This paper proposes a high-performance audio fingerprint extraction method for use in portable consumer devices. In the proposed method, a salient audio peak-pair fingerprint, based on a modulated complex lapped transform, improves the accuracy of the audio fingerprinting system in actual noisy environments with low computational complexity. Experimental results confirm that the proposed method is quite robust in different noise conditions and achieves promising preliminary accuracy results.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.1
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• pp.67-74
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• 2016

In this paper, we propose a watermarking technology for a mixed music. The mixed music means recreated music that contained a number of musics in one audio clip. Royalty associated with the audio content is typically imposed by the full audio content. However, the calculation of royalties gives rise to conflict between copyright holders and users in the mixed music because it uses not full audio content but a fraction of that. To solve the conflict related with the mixed music, we propose a audio watermarking technique that inserts different watermarks for each audio in the audio that make up the mixed music. The proposed watermarking scheme might have poor SNR (signal to noise ratio) to embed to each audio clip. To overcome poor SNR problem, we used inaudible pseudo random sequence which modifies typical pseudo random sequence to canonical signed digit (CSD) form. The proposed method verifies the performance by each watermark extraction and the time internal estimation valies from the mixed music.

• Journal of Broadcast Engineering
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• v.6 no.1
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• pp.3-12
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• 2001

Over the last few years, digital audio watermarking has become an interesting issue In many application areas, including digital broadcasting. This is primarily motivated by a need to provide copyright protection of digital audio content. Digital watermarking is a technique to embed copyright or other information int? the underlying data. Several possible audio watermarking techniques have been developed including spread spectrum watermarking, echo watermarking, phase coding, and patchwork. In this paper, we describe some requirements of digital audio watermarking as a tool for copyright protection of broadcasting content, and compare popular audio watermarking algorithms in some significant aspects.

• 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.