• Title/Summary/Keyword: Music Streaming

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Client-driven Animated Keyframe Generation System Using Music Analysis (음악 분석을 이용한 클라이언트 중심의 키프레임 생성 시스템)

  • Mujtaba, Ghulam;Kim, Seondae;Park, Eunsoo;Kim, Seunghwan;Ryu, Jaesung;Ryu, Eun-Seok
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2019.06a
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    • pp.173-175
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    • 2019
  • Animated images formats such as WebP are highly portable graphics formats that are being used everywhere on the Internet. Despite their small sizes and duration, WebP image previews the video without watching the entire content with minimum bandwidth. This paper proposed a novel method to generate personalized WebP images in the client side using its computation resources. The proposed system automatically extracts the WebP image from climax point using music analysis. Based on user interest, the system predicts the genre using Convolutional Neural Network (CNN). The proposed method can easily integrate with streaming platforms such as YouTube, Netflix, Hulu, and others.

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An Embedding /Extracting Method of Audio Watermark Information for High Quality Stereo Music (고품질 스테레오 음악을 위한 오디오 워터마크 정보 삽입/추출 기술)

  • Bae, Kyungyul
    • Journal of Intelligence and Information Systems
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    • v.24 no.2
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    • pp.21-35
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    • 2018
  • Since the introduction of MP3 players, CD recordings have gradually been vanishing, and the music consuming environment of music users is shifting to mobile devices. The introduction of smart devices has increased the utilization of music through music playback, mass storage, and search functions that are integrated into smartphones and tablets. At the time of initial MP3 player supply, the bitrate of the compressed music contents generally was 128 Kbps. However, as increasing of the demand for high quality music, sound quality of 384 Kbps appeared. Recently, music content of FLAC (Free License Audio Codec) format using lossless compression method is becoming popular. The download service of many music sites in Korea has classified by unlimited download with technical protection and limited download without technical protection. Digital Rights Management (DRM) technology is used as a technical protection measure for unlimited download, but it can only be used with authenticated devices that have DRM installed. Even if music purchased by the user, it cannot be used by other devices. On the contrary, in the case of music that is limited in quantity but not technically protected, there is no way to enforce anyone who distributes it, and in the case of high quality music such as FLAC, the loss is greater. In this paper, the author proposes an audio watermarking technology for copyright protection of high quality stereo music. Two kinds of information, "Copyright" and "Copy_free", are generated by using the turbo code. The two watermarks are composed of 9 bytes (72 bits). If turbo code is applied for error correction, the amount of information to be inserted as 222 bits increases. The 222-bit watermark was expanded to 1024 bits to be robust against additional errors and finally used as a watermark to insert into stereo music. Turbo code is a way to recover raw data if the damaged amount is less than 15% even if part of the code is damaged due to attack of watermarked content. It can be extended to 1024 bits or it can find 222 bits from some damaged contents by increasing the probability, the watermark itself has made it more resistant to attack. The proposed algorithm uses quantization in DCT so that watermark can be detected efficiently and SNR can be improved when stereo music is converted into mono. As a result, on average SNR exceeded 40dB, resulting in sound quality improvements of over 10dB over traditional quantization methods. This is a very significant result because it means relatively 10 times improvement in sound quality. In addition, the sample length required for extracting the watermark can be extracted sufficiently if the length is shorter than 1 second, and the watermark can be completely extracted from music samples of less than one second in all of the MP3 compression having a bit rate of 128 Kbps. The conventional quantization method can extract the watermark with a length of only 1/10 compared to the case where the sampling of the 10-second length largely fails to extract the watermark. In this study, since the length of the watermark embedded into music is 72 bits, it provides sufficient capacity to embed necessary information for music. It is enough bits to identify the music distributed all over the world. 272 can identify $4*10^{21}$, so it can be used as an identifier and it can be used for copyright protection of high quality music service. The proposed algorithm can be used not only for high quality audio but also for development of watermarking algorithm in multimedia such as UHD (Ultra High Definition) TV and high-resolution image. In addition, with the development of digital devices, users are demanding high quality music in the music industry, and artificial intelligence assistant is coming along with high quality music and streaming service. The results of this study can be used to protect the rights of copyright holders in these industries.

Reinventing the revenue model for the content platform (콘텐츠 플랫폼의 수익모델 혁신 전략에 대한 고찰)

  • Choi, Kwang-Hun;Kim, Junic
    • Journal of Digital Contents Society
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    • v.18 no.7
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    • pp.1267-1280
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    • 2017
  • This study examines the changes of the online music market and revenue models by the theory of network society and communications of Manuel Castells for the content platform. As a result of this study, we found that active communications among the members in the network, played a crucial role in the creation of contents and the promotions of profit for platform providers. It is especially important to create an environment in which members can voluntarily communicate rather than an artificial control. The content platform business consists of people, thus it has been proven that providing play elements of culture and society are important, as well as necessary conditions to the generation related to content based platform businesses.

Analysis of Game Video Production in Streaming Media Environment (스트리밍 환경에서 게임 영상 제작 분석)

  • Lee, JianBo;Ryu, Seuc-Ho;Hyun, Seung-Hoon
    • Journal of Industrial Convergence
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    • v.20 no.5
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    • pp.69-76
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    • 2022
  • This paper summarizes the features and functions of game video on each platform through a study on streaming technology. Game videos have a high relationship with game content itself for the purpose of marketing and disseminating game play methods using games as the subject matter. The video length is short and it is easy to spread. The main types of game video content are game commentary, game strategy, funny, imitative, music video, and game information. As a game promotion video function, etc., it is used as a direct or indirect publicity for the game by the producer and the user for each reason. This article analyzed the production subject and production conditions of game videos, focusing on the production process. The production subject is divided into professional creators, non-professional creators, and general users. The motive for producing game videos is mainly to obtain economic benefits. The production process was extracted and presented through examples of game videos.

Research on hybrid music recommendation system using metadata of music tracks and playlists (음악과 플레이리스트의 메타데이터를 활용한 하이브리드 음악 추천 시스템에 관한 연구)

  • Hyun Tae Lee;Gyoo Gun Lim
    • Journal of Intelligence and Information Systems
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    • v.29 no.3
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    • pp.145-165
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    • 2023
  • Recommendation system plays a significant role on relieving difficulties of selecting information among rapidly increasing amount of information caused by the development of the Internet and on efficiently displaying information that fits individual personal interest. In particular, without the help of recommendation system, E-commerce and OTT companies cannot overcome the long-tail phenomenon, a phenomenon in which only popular products are consumed, as the number of products and contents are rapidly increasing. Therefore, the research on recommendation systems is being actively conducted to overcome the phenomenon and to provide information or contents that are aligned with users' individual interests, in order to induce customers to consume various products or contents. Usually, collaborative filtering which utilizes users' historical behavioral data shows better performance than contents-based filtering which utilizes users' preferred contents. However, collaborative filtering can suffer from cold-start problem which occurs when there is lack of users' historical behavioral data. In this paper, hybrid music recommendation system, which can solve cold-start problem, is proposed based on the playlist data of Melon music streaming service that is given by Kakao Arena for music playlist continuation competition. The goal of this research is to use music tracks, that are included in the playlists, and metadata of music tracks and playlists in order to predict other music tracks when the half or whole of the tracks are masked. Therefore, two different recommendation procedures were conducted depending on the two different situations. When music tracks are included in the playlist, LightFM is used in order to utilize the music track list of the playlists and metadata of each music tracks. Then, the result of Item2Vec model, which uses vector embeddings of music tracks, tags and titles for recommendation, is combined with the result of LightFM model to create final recommendation list. When there are no music tracks available in the playlists but only playlists' tags and titles are available, recommendation was made by finding similar playlists based on playlists vectors which was made by the aggregation of FastText pre-trained embedding vectors of tags and titles of each playlists. As a result, not only cold-start problem can be resolved, but also achieved better performance than ALS, BPR and Item2Vec by using the metadata of both music tracks and playlists. In addition, it was found that the LightFM model, which uses only artist information as an item feature, shows the best performance compared to other LightFM models which use other item features of music tracks.

Copyright Protection using Encryption of DCT Coefficients and Motion Vector in Video Codec of Mobile Device (모바일 기기내의 비디오 코덱에서 DCT 계수와 움직임 벡터의 암호화를 이용한 저작권 보호)

  • Kwon, Goo Rak;Kim, Young Ro
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.4 no.1
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    • pp.41-46
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    • 2008
  • With widespread use of the Internet and improvements in streaming media and compression technology, digital music, video, and image can be distributed instantaneously across the Internet to end-users. However, most conventional Digital Right Management are often not secure and fast enough to process the vast amount of data generated by the multimedia applications to meet the real-time constraints. In this paper, we propose the copyright protection using encryption of DCT coefficients and motion vector in MPEG-4 video codec of mobile device. This paper presents a new Digital Rights Management that modifies the Motion Vector of Macroblock for mobile device. Experimental results indicate that the proposed DRM can not only achieve very low cost of the encryption but also enable separable authentication to individual mobile devices such as Portable Multimedia Player and Personal Digital Assistants. The performance of the proposed methods have low complexity and low increase of bit rate in overhead.

Simulation Study on the Stream Server for Deciding the Priority for Using Resources (스트림 서버에서 자원 사용 우선순위 결정을 위한 시뮬레이션 연구)

  • 박진원
    • Journal of the Korea Society for Simulation
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    • v.12 no.4
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    • pp.95-102
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    • 2003
  • Stream servers are for supplying multimedia stream data to users through the internet such as movies and music without discontinuation. A typical stream server is designed roughly by considering the characteristics of stream services and by employing processors, memory, PCI bus, Ethernet, TOE and disks. This study focuses on deciding the priority for using resources such as PCI bus, buffer memory and TOE buffer, which have limited capacities in a typical stream server. When the priorities for using limited resources are not given properly, the stream servers may not even function as originally designed. The simulation study shows that the top priority for using PCI bus for normal streaming services should be given to the operation that sends data from buffer memory to TOE buffer. Giving priority for using PCI bus to other operation such as sending data from disks to memory results in a deadlock phenomenon.

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Development of the platform independent music streaming web services based HTML5 (플렛폼 독립적인 HTML5 기반의 음원 스트리밍 웹서비스 개발)

  • Choi, Jae-Sung;Kwon, Hang-Geul;Park, Si-Hong;Baek, Tae-San
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.11a
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    • pp.955-957
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    • 2014
  • HTML5에 들어서면서 웹서비스 구현에 보편적으로 사용되는 신기술들이 속속들이 나오고 있다. 브라우저 자체적인 그래픽 구현을 위한 Canvas/SVG, 멀티미디어와 관련된 audio, video, webaudio API 등이 추가되었고, 이로 인해 HTML5는 웹 환경에 더 빠르고 정교하며 편리한 인터페이스를 제공해 주었다. 이 중 아직도 표준화가 진행 중이거나 많은 브라우저에서 지원하지 않아 섣불리 사용 할 수 없는 기술들 또한 상당 수 존재한다. 본 논문에서 HTML5기술들을 활용하여 다양한 플랫폼에서 공통적으로 동작되는 플랫폼 독립적인 음원 스트리밍 웹서비스를 개발한다.

Noise Robust Text-Independent Speaker Identification for Ubiquitous Robot Companion (지능형 서비스 로봇을 위한 잡음에 강인한 문맥독립 화자식별 시스템)

  • Kim, Sung-Tak;Ji, Mi-Kyoung;Kim, Hoi-Rin;Kim, Hye-Jin;Yoon, Ho-Sub
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.190-194
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    • 2008
  • This paper presents a speaker identification technique which is one of the basic techniques of the ubiquitous robot companion. Though the conventional mel-frequency cepstral coefficients guarantee high performance of speaker identification in clean condition, the performance is degraded dramatically in noise condition. To overcome this problem, we employed the relative autocorrelation sequence mel-frequency cepstral coefficient which is one of the noise robust features. However, there are two problems in relative autocorrelation sequence mel-frequency cepstral coefficient: 1) the limited information problem. 2) the residual noise problem. In this paper, to deal with these drawbacks, we propose a multi-streaming method for the limited information problem and a hybrid method for the residual noise problem. To evaluate proposed methods, noisy speech is used in which air conditioner noise, classic music, and vacuum noise are artificially added. Through experiments, proposed methods provide better performance of speaker identification than the conventional methods.

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A system for recommending audio devices based on frequency band analysis of vocal component in sound source (음원 내 보컬 주파수 대역 분석에 기반한 음향기기 추천시스템)

  • Jeong-Hyun, Kim;Cheol-Min, Seok;Min-Ju, Kim;Su-Yeon, Kim
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.6
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    • pp.1-12
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    • 2022
  • As the music streaming service and the Hi-Fi market grow, various audio devices are being released. As a result, consumers have a wider range of product choices, but it has become more difficult to find products that match their musical tastes. In this study, we proposed a system that extracts the vocal component from the user's preferred sound source and recommends the most suitable audio device to the user based on this information. To achieve this, first, the original sound source was separated using Python's Spleeter Library, the vocal sound source was extracted, and the result of collecting frequency band data of manufacturers' audio devices was shown in a grid graph. The Matching Gap Index (MGI) was proposed as an indicator for comparing the frequency band of the extracted vocal sound source and the measurement data of the frequency band of the audio devices. Based on the calculated MGI value, the audio device with the highest similarity with the user's preference is recommended. The recommendation results were verified using equalizer data for each genre provided by sound professional companies.