MIDI: a comprehensive introduction
MIDI: a comprehensive introduction
Fundamentals of speech recognition
Fundamentals of speech recognition
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
Manipulation of music for melody matching
MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
Automatic Segmentation of Acoustic Musical Signals Using Hidden Markov Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Musical information retrieval using melodic surface
Proceedings of the fourth ACM conference on Digital libraries
Towards a digital library of popular music
Proceedings of the fourth ACM conference on Digital libraries
Evaluating automatic melody segmentation aimed at music information retrieval
Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries
The Musical Archive Information System at Teatro alla Scala
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Annotating illuminated manuscripts: an effective tool for research and education
Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries
Music retrieval: a tutorial and review
Foundations and Trends in Information Retrieval
ECDL'10 Proceedings of the 14th European conference on Research and advanced technology for digital libraries
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Music digital libraries pose interesting and challenging research problems, in particular for the development of methodologies and tools for the retrieval of music documents. One difficult aspect of content-based retrieval of musical works is that only scores can be represented by a symbolic notation, while performances, which are of interest for the majority of users, allow for access based on bibliographic values only. The research work reported in this paper proposes to index and retrieve music performances through an automatic alignment of acoustic recordings with the music scores. Alignment my allow for: automatic recognition of performances, aimed at cataloging large collections of recordings; automatic tagging of performances, aimed at an easy access to long recordings. The methodology is based on the use of hidden Markov models, a powerful tool that has been successfully used in many research areas, like speech recognition and molecular biology. The approach has been tested on a collection of acoustic and synthetic performances, showing good results in the recognition and in the tagging of performances. The proposed approach can be used to increase the functionalities of a music digital library, allowing for content-based access to scores and recordings.