• The KIPS Transactions:PartB
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• v.17B no.2
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• pp.99-106
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• 2010

In this paper, we propose the construction of multi-queries and consistency principle for the user's emotion-based music retrieval system. The features used in the system are MPEG-7 audio descriptors, which are international standards recommended for content-based audio retrievals. In addition we propose the method to determine the weight that represent the importance of each descriptor for each emotion in order to reduce the computation. Also, the proposed retrieval algorithm that uses the relevance feedback based on consistency principal and multi-queries improves the success ratio of musics corresponding to user's emotion.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.73-79
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• 2010

Emotion intelligence computing is able to processing of human emotion through it's studying and adaptation. Also, Be able more efficient to interaction of human and computer. As sight and hearing, music & image is constitute of short time and continue for long. Cause to success marketing, understand-translate of humanity emotion. In this paper, Be design of check system that matched music and image by user emotion keyword(irritability, gloom, calmness, joy). Suggested system is definition by 4 stage situations. Then, Using music & image and emotion ontology to retrieval normalized music & image. Also, A sampling of image peculiarity information and similarity measurement is able to get wanted result. At the same time, Matched on one space through pared correspondence analysis and factor analysis for classify image emotion recognition information. Experimentation findings, Suggest system was show 82.4% matching rate about 4 stage emotion condition.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.2
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• pp.124-128
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• 2011

Music emotion recognition is currently one of the most attractive research areas in music information retrieval. In order to use emotion as clues when searching for a particular music, several music based emotion recognizing systems are fundamentally utilized. In order to maximize user satisfaction, the recognition accuracy is very important. In this paper, we develop a new music emotion recognition system, which employs a multilabel feature selector and multilabel classifier. The performance of the proposed system is demonstrated using novel musical emotion data.

• Journal of the Korea Society of Computer and Information
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• v.18 no.5
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• pp.43-52
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• 2013

In recent years, a large amount of music content is distributed in the Internet environment. In order to retrieve the music content effectively that user want, various studies have been carried out. Especially, it is also actively developing music recommendation system combining emotion model with MIR(Music Information Retrieval) studies. However, in these studies, there are several drawbacks. First, structure of emotion model that was used is simple. Second, because the emotion model has not designed for Korean language, there is limit to process the semantic of emotional words expressed with Korean. In this paper, through extending the existing emotion model, we propose a new emotion model KOREM(KORean Emotional Model) based on Korean. And also, we design and implement ontology using emotion model proposed. Through them, sorting, storage and retrieval of music content described with various emotional expression are available.

• Journal of Korea Game Society
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• v.17 no.3
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• pp.45-52
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• 2017

This paper proposes a new strategy of emotion-based music visualization. Emotional LED lighting control system is suggested to help audiences enhance the musical experience. In the system, emotion in music is recognized by a proposed algorithm using a dimensional approach. The algorithm used a method of music emotion variation detection to overcome some weaknesses of Thayer's model in detecting emotion in a one-second music segment. In addition, IRI color model is combined with Thayer's model to determine LED light colors corresponding to 36 different music emotions. They are represented on LED lighting control system through colors and animations. The accuracy of music emotion visualization achieved to over 60%.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06d
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• pp.153-155
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• 2011

최근 음악 검색 연구에서 일반적으로 사용되는 방법은 키워드 중심의 텍스트 기반 검색방식, 음원의 특징 정보나 허밍 질의 처리 등을 이용하는 내용기반 검색 방식 등이 있다. 그러나 이러한 검색 방식은 단순히 원하는 음악을 질의에 따라 검색해 주며 인간의 감성을 고려하지 못하고 있다. 따라서 본 논문에서는 질의에 의한 검색뿐만 아니라 질의한 음원과 감성정도가 같은 음원을 추천하는 인간 감성 기반 음악 검색 및 추천 시스템을 제안한다. 인간 감성 기반 음악 검색 및 추천 시스템은 크게 2가지 요소로 구성된다. 첫 번째는 사용자가 질의한 질의어를 분석하는 감성기반 검색추론엔진과 두 번째는 음원의 특징 정보 및 감성 정보를 가지고 있는 음원 감성 정보 데이터베이스로 구성된다. 사용자의 감성에 따라 음악을 검색하고 추천한다는 것은 향후 음반 산업에 큰 발전에 기여할 것으로 기대한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.51-53
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• 2008

최근 오디오 압축 기술의 발전에 힘입은 디지털 음원과 웹 스트리밍의 보급으로, 사용자가 음악 정보에 손쉽게 접할 수 있게 되었다. 이에 따라 음악을 보다 쉽고 효율적인 방법으로 검색하는 방법뿐 아니라 사용자의 환경에 따라 적절한 음악을 검색할 수 있는 기능의 필요성이 증가하게 되었다. 본 논문에서는 음악의 특징에 따라 분류된 데이터베이스를 사용하고, 사용자의 감정을 분석하여 적절한 음악을 검색하는 시스템을 제안한다. 본 시스템은 사용자의 감정 입력을 효율적으로 처리하기 위한 방법으로 Thayer의 2D emotional space를 적용하여 Valence-Arousal model의 두 가지의 입력을 처리한다. 가장 적합한 음악의 정보를 얻기 위해 사용된 Fuzzy Inference System의 IF-THEN 규칙을 정의하기 위하여 언어적으로 정의된 기존의 음악 감정 연구 결과를 적용하였고, 도출된 결과와 가장 유사도가 깊은 음악을 우선적으로 검색하도록 설계하였다. 이와 같이 구현된 시스템의 타당성을 검증하기 위해 사용자 설문조사를 수행하였다.