Query by humming: musical information retrieval in an audio database
Proceedings of the third ACM international conference on Multimedia
Towards the digital music library: tune retrieval from acoustic input
Proceedings of the first ACM international conference on Digital libraries
Music retrieval as text retrieval (poster abstract): simple yet effective
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Visualizing music and audio using self-similarity
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
Independent component analysis: algorithms and applications
Neural Networks
A practical query-by-humming system for a large music database
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Query Similar Music by Correlation Degree
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Music summarization using key phrases
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
Fast and robust fixed-point algorithms for independent component analysis
IEEE Transactions on Neural Networks
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An approach to retrieval popular song by singing matching is presented in this paper. Vocal singing is the dominant part in popular song, after extracting singing from monaural or stereo recording of popular song by independent components analysis, MFCC feature is calculated on it, self-similarity sequence is constructed on this feature, recurrent neural network is employed to remember the self-similarity sequence, self-similarity sequence is also constructed on input singing, the weights of recurrent neural network are used as indices on music database, retrieval list is generated by correlation degree of self-similarity sequence. Preliminary experiment result shows the effectiveness of our approach.