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EMIR: A novel emotion-based music retrieval system

Zhou, Lijuan Marissa and Lin, Hongfei and Gurrin, Cathal (2012) EMIR: A novel emotion-based music retrieval system. In: The 18th International Conference on Multimedia Modeling, 4-6 Jan 2012, Klagenfurt, Austria.

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Music is inherently expressive of emotion meaning and affects the mood of people. In this paper, we present a novel EMIR (Emotional Music Information Retrieval) System that uses latent emotion elements both in music and non-descriptive queries (NDQs) to detect implicit emotional association between users and music to enhance Music Information Retrieval (MIR). We try to understand the latent emotional intent of queries via machine learning for emotion classification and compare the performance of emotion detection approaches on different feature sets. For this purpose, we extract music emotion features from lyrics and social tags crawled from the Internet, label some for training and model them in high-dimensional emotion space and recognize latent emotion of users by query emotion analysis. The similarity between queries and music is computed by verified BM25 model.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:Music Information Retrieval; Emotion Detection; Machine Learning; Human Computer Interaction
Subjects:Computer Science > Information technology
Computer Science > Artificial intelligence
Medical Sciences > Psychology
Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:17532
Deposited On:01 Oct 2012 16:32 by Ms Lijuan Marissa Zhou. Last Modified 15 Feb 2017 15:33

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