Lemström, K., Ukkonen, E.: Including interval encoding into edit distance based music comparison and retrieval. In: Proceeding of the Joint 11th Sound and Music Computing Conference (SMC) and 40th International Computer Music Conference (ICMC), Athens, Greece (2014) Kaliakatsos-Papakostas, M., Cambouropoulos, E.: Probabilistic harmonisation with fixed intermediate chord constraints. In: Proceedings of the 16th International Society for Music Information Retrieval (ISMIR) Conference, Malaga, Spain (2015)
Kaliakatsos-Papakostas, M., Zacharakis, A., Tsougras, C., Cambouropoulos, E.: Evaluating the general chord type representation in tonal music and organising GCT chord labels in functional chord categories. Kaliakatsos-Papakostas, M., Queiroz, M., Tsougras, C., Cambouropoulos, E.: Conceptual blending of harmonic spaces for creating melodic harmonisation. Kaliakatsos-Papakostas, M., Cambouropoulos, E.: Conceptual blending of high-level features and data-driven salience computation in melodic generation. Hubbard, T.L., Datteri, D.L.: Recognizing the Component tones of a major chord. Herremans, D., Chuan, C.-H.: The emergence of deep learning: new opportunities for music and audio technologies. Gray, P., Bunescu, R.: From note-level to chord-level neural network models for voice separation in symbolic music (2020). In: Aramaki, M., Derrien, O., Kronland-Martinet, R., Ystad, S. Giraud, M., Déguernel, K., Cambouropoulos, E.: Fragmentations with pitch, rhythm and parallelism constraints for variation matching. Garnelo, M., Shanahan, M.: Reconciling deep learning with symbolic artificial intelligence: representing objects and relations. In: Proceedings of the Joint 11th Sound and Music Computing Conference (SMC) and 40th International Computer Music Conference (ICMC), Athens, Greece (2014) Ĭambouropoulos, E., Kaliakatsos-Papakostas, M., Tsougras, C.: An idiom-independent representation of chords for computational music analysis and generation. Oxford University Press (forthcoming)Ĭambouropoulos, E.: The harmonic musical surface and two novel chord representation schemes. In: Shanahan, D., Burgoyne, J.A., Quinn, I., (eds.) The Oxford Handbook of Music and Corpus Studies. Springer (forthcoming)Ĭambouropoulos, E., Kaliakatsos-Papakostas, M.: Symbolic approaches and methods for analyzing similarity.
In: Miranda, E.R., (ed.) Handbook for Artificial Intelligence in Music. Springer, Heidelberg (2020)Ĭambouropoulos, E., Kaliakatsos-Papakostas, M.: Cognitive musicology and artificial intelligence: harmonic analysis, learning and generation. MIT Press, Cambridge (1994)īriot, J.P., Hadjeres, G., Pachet, F.: Deep learning techniques for music generation. īregman, A.S.: Auditory Scene Analysis: The Perceptual Organization of Sound. 2), 37–54 (2013)īenetos, E., Dixon, S., Giannoulis, D., Kirchhoff, H., Klapuri, A.: Automatic music transcription: challenges and future directions. īendixen, A., Bőhm, T.M., Szalárdy, O., Mill, R., Denham, S.L., Winkler, I.: Different roles of similarity and predictability in auditory stream segregation.
In: Iliadis, L., Maglogiannis, I., Papadopoulos, H., Karatzas, K., Sioutas, S. Barton, C., Cambouropoulos, E., Iliopoulos, C.S., Lipták, Z.: Melodic string matching via interval consolidation and fragmentation.
0 kommentar(er)
