Elements of information theory
Elements of information theory
Fundamentals of speech recognition
Fundamentals of speech recognition
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
A Large-Scale Evaluation of Acoustic and Subjective Music-Similarity Measures
Computer Music Journal
Learning the meaning of music
Computer
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple Bernoulli relevance models for image and video annotation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Music emotion recognition: the role of individuality
Proceedings of the international workshop on Human-centered multimedia
Large-scale content-based audio retrieval from text queries
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Combining audio content and social context for semantic music discovery
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
CompositeMap: a novel framework for music similarity measure
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
CompositeMap: a novel music similarity measure for personalized multimodal music search
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Clustering for music search results
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
On the use of anti-word models for audio music annotation and retrieval
IEEE Transactions on Audio, Speech, and Language Processing
Exploring automatic music annotation with "acoustically-objective" tags
Proceedings of the international conference on Multimedia information retrieval
A document-centered approach to a natural language music search engine
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Effective music tagging through advanced statistical modeling
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Three web-based heuristics to determine a person's or institution's country of origin
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Large-scale music tag recommendation with explicit multiple attributes
Proceedings of the international conference on Multimedia
ATLAS: a probabilistic algorithm for high dimensional similarity search
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
A Probabilistic Model to Combine Tags and Acoustic Similarity for Music Retrieval
ACM Transactions on Information Systems (TOIS)
Music retagging using label propagation and robust principal component analysis
Proceedings of the 21st international conference companion on World Wide Web
Supervised dictionary learning for music genre classification
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
Modeling concept dynamics for large scale music search
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
The Study of Content Security for Mobile Internet
Wireless Personal Communications: An International Journal
Context-aware mobile music recommendation for daily activities
Proceedings of the 20th ACM international conference on Multimedia
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Query-by-semantic-description (QBSD)is a natural paradigm for retrieving content from large databases of music. A major impediment to the development of good QBSD systems for music information retrieval has been the lack of a cleanly-labeled, publicly-available, heterogeneous data set of songs and associated annotations. We have collected the Computer Audition Lab 500-song (CAL500) data set by having humans listen to and annotate songs using a survey designed to capture 'semantic associations' between music and words. We adapt the supervised multi-class labeling (SML) model, which has shown good performance on the task of image retrieval, and use the CAL500 data to learn a model for music retrieval. The model parameters are estimated using the weighted mixture hierarchies expectation-maximization algorithm which has been specifically designed to handle real-valued semantic association between words and songs, rather than binary class labels. The output of the SML model, a vector of class-conditional probabilities, can be interpreted as a semantic multinomial distribution over a vocabulary. By also representing a semantic query as a query multinomial distribution, we can quickly rank order the songs in a database based on the Kullback-Leibler divergence between the query multinomial and each song's semantic multinomial. Qualitative and quantitative results demonstrate that our SML model can both annotate a novel song with meaningful words and retrieve relevant songs given a multi-word, text-based query.