An overview of audio information retrieval
Multimedia Systems - Special issue on audio and multimedia
Content-Based Classification, Search, and Retrieval of Audio
IEEE MultiMedia
Audio Content Description in Sound Databases
WI '01 Proceedings of the First Asia-Pacific Conference on Web Intelligence: Research and Development
Application of Temporal Descriptors to Musical Instrument Sound Recognition
Journal of Intelligent Information Systems
Construction and Evaluation of a Robust Multifeature Speech/Music Discriminator
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 2 - Volume 2
MARSYAS: a framework for audio analysis
Organised Sound
MARSYAS: a framework for audio analysis
Organised Sound
Musical instrument recognition using cepstral coefficients and temporal features
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
Sound analysis using MPEG compressed audio
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
Inmamusys: Intelligent multiagent music system
Expert Systems with Applications: An International Journal
The domain of acoustics seen from the rough sets perspective
Transactions on rough sets VI
Machine Recognition of Music Emotion: A Review
ACM Transactions on Intelligent Systems and Technology (TIST)
Parametrisation and correlation analysis applied to music mood classification
International Journal of Computational Intelligence Studies
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In recent years, there has been a tremendous need for the ability to query and process vast quantities of musical data. Automatic content extraction is clearly needed here, relating to various aspects of music. One of desirable options is the ability of identifying musical pieces representing different types of emotions, which music clearly evokes. This paper focuses on scrupulous planning of experiments on automatic recognition of emotions in music. Collecting and labelling of data, extraction of objective features, as well as classification and cross-validation methods are proposed and discussed.