Bibliograafia: diginootide teemaga haakuvaid publikatsioone




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Bibliograafia: diginootide teemaga haakuvaid publikatsioone


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2013





  1. Proceedings of the 14th International Society for Music Information Retrieval Con­ference (eds Alceu de Souza Britto Jr and Gouyon, Fabien and Dixon, Simon) November 4-8, 2013, Curitiba, Brazil, 612 p.

http://www.ppgia.pucpr.br/ismir2013/proceedings/

pp 125-130. Gabriel Vigliensoni, Gregory Burlet, and Ichiro Fujinag

Optical Measure Recognition In Common Music Notation http://www.ppgia.pucpr.br/ismir2013/wp-content/uploads/2013/09/207_Paper.pdf


2012





  1. Müller, Meinard and Goto, Masataka and Markus Schedl (eds). Multimodal Music Processing. Dagstuhl Publishing Follow-Ups - Vol.3, 2012, 245 p.

http://drops.dagstuhl.de/opus/volltexte/dfu-complete/dfu-vol3-complete.pdf

The volume is devoted to the topic of multimodal music processing, where both the availability of multiple, complementary sources of music-related information and the role of the human user is considered. It is based on Dagstuhl seminar on “Multimodal Music Processing” held in January 2011.

  1. Damm, David and Fremerey, Christian and Thomas, Verena and Clausen, Michael and Kurth, Frank and Müller, Meinard. A Digital Library Framework for Heterogeneous Music Collections – from Document Acquisition to Cross-Modal Interaction. International Journal on Digital Libraries: Special Issue on Digital Music Libraries, 2012. 20 p. (to appear)

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  1. Böck, Sebastian and   Krebs, Florian and   Schedl, Markus. Evaluating the Online Capabilities of Onset Detection Methods 13th International Society for Music Information Retrieval Conference, October 8-12, 2012, Porto, Portugal, 49-54. Capabilities of Onset Detection Methods, October 8th-12th / Evaluates various onset detection algorithms in terms of their online capabilities. Most methods use some kind of normalization over time, which renders them unusable for online tasks. Modifications of existing methods to enable online application and evaluation their performance on a large dataset consisting of 27,774 annotated onsets. Focuses particularly on the incorporated preprocessing and peak detection methods. Shows that, with the right choice of parameters, the maximum achievable performance is in the same range as that of offline algorithms, and that preprocessing can improve the results considerably. Proposes a new onset detection method based on the common spectral flux and a new peak-picking method which outperforms traditional methods both online and offline and works with audio signals of various volume levels. /

  2. Grosche,  Peter and Serrà,  Joan and Müller, Meinard and   Arcos, Josep Lluis Structure-Based Audio Fingerprinting for Music Retrieval . 13th International Society for Music Information Retrieval Conference, October 8-12, 2012, Porto, Portugal, 55-60. / Introduces the concept of structure fingerprints, which are compact descriptors of the musical structure of an audio recording. Given a recorded music performance, structure fingerprints facilitate the retrieval of other performances sharing the same underlying structure. Avoiding any explicit determination of musical structure, these fingerprints can be thought of as a probability density function derived from a self-similarity matrix. It is shown that the proposed fingerprints can be compared by using simple Euclidean distances without using any kind of complex warping operations required in previous approaches. /

  3. Izmirli, Ozgur and Sharma, Gyanendra. Bridging Printed Music and Audio Through Alignment Using a Mid-level Score Representation 13th International Society for Music Information Retrieval Conference, October 8-12, 2012, Porto, Portugal, 61-66. / A system that utilizes a mid-level score representation for aligning printed music to its audio rendition. The mid-level representation is designed to capture an approximation to the musical events present in the printed score. It consists of a template based note detection frontend that seeks to detect notes without regard to musical duration, accidentals or the key signature. The presented method is designed for the commonly used grand staff and the approach is extendable to other types of scores. /

  4. Yoshii, Kazuyoshi and Goto, Masataka. Infinite Composite Autoregressive Models for Music Signal Analysis 13th International Society for Music Information Retrieval Conference, October 8-12, 2012, Porto, Portugal, 79-84. / Presents novel probabilistic models that can be used to estimate multiple fundamental frequencies from polyphonic audio signals /

  5. Burlet, Gregory and   Porter, Alastair and    Hankinson, Andrew and   Fujinaga, Ichiro Neon.js: Neume Editor Online 13th International Society for Music Information Retrieval Conference, October 8-12, 2012, Porto, Portugal, 121-126. / Introduces Neon.js, a browser-based music notation editor written in JavaScript. The editor can be used to manipulate digitally encoded musical scores in square-note notation. This type of notation presents certain challenges to a music notation editor, since many neumes (groups of pitches) are ligatures—continuous graphical symbols that represent multiple notes. Neon.js will serve as a component within an online optical music recognition framework. The primary purpose of the editor is to provide a readily accessible interface to easily correct errors made in the process of optical music recognition /

  6. Wülfing, Jan and Riedmiller, Martin Unsupervised Learning of Local Features for Music Classification 13th International Society for Music Information Retrieval Conference, October 8-12, 2012, Porto, Portugal, 139-144. / Investigates the applicability of unsupervised feature learning methods to the task of automatic genre prediction of music pieces. More specifically we evaluate a framework that recently has been successfully used to recognize objects in images. /

  7. Joder, Cyril and Schuller, Bjoern Score-Informed Leading Voice Separation from Monaural Audio . 13th International Society for Music Information Retrieval Conference, October 8-12, 2012, Porto, Portugal, 277-282. / Presents a novel application of this idea for leading voice separation exploiting a temporally aligned MIDI Score /

  8. Arzt, Andreas and Böck, Sebastian and Widmer, Gerhard Fast Identification of Piece and Score Position via Symbolic Fingerprinting. International Society for Music Information Retrieval Conference, October 8-12, 2012, Porto, Portugal, 433-438. / Presents a novel algorithm that, given a short snippet of an audio performance (piano music, for the time being), identifies the piece and the score position. Instead of using audio matching methods proposes a combination of a state-of-the-art music transcription algorithm and a new symbolic fingerprinting method. The resulting system is usable in both on-line and off-line scenarios and thus may be of use in many application areas. The system operates with only minimal lag and achieves high precision even with very short queries. / http://www.cp.jku.at/research/papers/Arzt_etal_ISMIR_2012.pdf

  9. Bosch, Juan J. and   Janer, Jordi and   Fuhrmann,  Ferdinand and Herrera, Perfecto. A Comparison of Sound Segregation Techniques for Predominant Instrument Recognition in Musical Audio Signals . 13th International Society for Music Information Retrieval Conference, October 8-12, 2012, Porto, Portugal, 559-564. / Addresses the identification of predominant music instruments in polytimbral audio by previously dividing the original signal into several streams. /

  10. Sébastien, Véronique and   Ralambondrainy, Henri and   Sébastien, Olivier and    Conruyt, Noël. Score Analyzer: Automatically Determining Scores Difficulty Level for Instrumental e-Learning . 13th International Society for Music Information Retrieval Conference, October 8-12, 2012, Porto, Portugal, 571-576. / Proposes a Score Analyzer prototype in order to automatically extract the difficulty level of a MusicXML piece and suggest advice thanks to a Musical Sign Base. /

  11. Ting-Ting Chou and Wen-Chieh Chen and Siang-An Wnag and Ken-Ning Chang and Herng-Yow Chen. Real-Time Polyphonic Score Following System. IEEE International Conference on Multimedia and Expo Workshops, 2012, 205-210 http://ieeexplore.ieee.org/iel5/6265868/6266221/06266256.pdf?arnumber=6266256 . / Proposes an efficient score tracking system that can track musical performance on a score in real time. It can be used in wide range of applications. The algorithm is like Dannenberg’s Dynamic Programming algorithm but extends his algorithm to process polyphony music. Ideally, the notes of polyphony have to be played at the same time. But when the notes are played, there are tiny differences among the time. The algorithm groups nearly played note and classifies them into leading notes and following notes. The algorithm, adopting Oshima’s coping with four types of errors, also takes in consideration some performer’s habits and circumstances, such as repeating unfamiliar parts or playing the wrong note. /
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