Biblio

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Srinivasamurthy, A., & Chordia P. (2012).  A Unified System for Analysis and Representation of Indian Classical Music using Humdrum Syntax. 2nd CompMusic Workshop.
application/pdf iconCompMusicWorkshop_2.pdf
Srinivasamurthy, A., Holzapfel A., Cemgil A. T., & Serra X. (2015).  Particle Filters for Efficient Meter Tracking with Dynamic Bayesian Networks. 16th International Society for Music Information Retrieval (ISMIR) Conference. 197-203. Abstract
Srinivasamurthy, A., Holzapfel A., & Serra X. (2014).  In Search of Automatic Rhythm Analysis Methods for Turkish and Indian Art Music. Journal of New Music Research. 43(1), 94-114. Abstract
Srinivasamurthy, A., Holzapfel A., Ganguli K. K., & Serra X. (2017).  Aspects of tempo and rhythmic elaboration in Hindustani music: A corpus study. Frontiers in Digital Humanities: Digital Musicology. 4, 20. Abstract
Srinivasamurthy, A., Holzapfel A., Cemgil A. T., & Serra X. (2016).  A generalized Bayesian model for tracking long metrical cycles in acoustic music signals. 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016). 76-80. Abstract
Srinivasamurthy, A., & Chordia P. (2012).  Multiple Viewpoint Modeling of North Indian Classical Vocal Compositions. Proceedings of the 9th International Symposium on Computer Music Modeling and Retrieval (CMMR).
application/pdf iconCMMR2012.pdf
Srinivasamurthy, A. (2016).  A Data-driven Bayesian Approach to Automatic Rhythm Analysis of Indian Art Music. Department of Information and Communication Technologies. 332. Abstract
Srinivasamurthy, A., Koduri G. K., Gulati S., Ishwar V., & Serra X. (2014).  Corpora for Music Information Research in Indian Art Music. International Computer Music Conference/Sound and Music Computing Conference. 1029-1036. Abstract
Stamatopoulos, C. (2009).  Harmonic Audio Object Processing in Time Domain. Abstract
Stamellos, L. (2016).  Freesound drum sets using unconventional sounds. Abstract
Stanyek, J., Benadon F., Browner T., Chordia P., Danielsen A., Gómez E., et al. (2014).  Forum on transcription. Twentieth-Century Music. 11(1), 101-161.
Stella, A. (2012).  Auditory Display of Brain Oscillatory Activity with Electroencephalography. Abstract
application/pdf iconAndrew-Stella-SMC-Master-Thesis.pdf
Stowell, D., Musevic S., Bonada J., & Plumbey M. (2013).  Improved Multiple Birdsong Tracking with Distribution Derivative Method and Markov Renewal Process Clustering. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP).
Streich, S., & Herrera P. (2005).  Detrended Fluctuation Analysis of Music Signals Danceability Estimation and further Semantic Characterization. AES 118th Convention. Abstract
Streich, S., & Herrera P. (2004).  Toward Describing Perceived Complexity of Songs Computational Methods and Implementation. 25th AES International Conference: Metadata for Audio . Abstract
application/pdf iconStreich-AES25-2004.pdf
Streich, S. (2007).  Music Complexity a multi-faceted description of audio content. Department of Information and Communication Technologies. Abstract
Streich, S. (2005).  Automatic Characterization of Music Complexity a multi-faceted approach. Abstract
Streich, S., & Herrera P. (2006).  Algorithmic Prediction of Music Complexity Judgements. 9th International Conference on Music Perceptionand Cognition. Abstract
Suárez, A. M. (2015).  Reducing Bias in the Probabilistic Evaluation of Audio Music Similarity. Abstract
application/pdf iconAdriana-Suarez-Master-thesis-2015.pdf
Suros, L. (2019).  Clustering of multiple-event online sound collections with the codebook approach. Abstract
Susini, P., Misdariis N., Lemaitre G., Houix O., Rocchesso D., Polotti P., et al. (2006).  Closing the loop of sound evaluation and design. Perceptual Quality of Systems. Abstract
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