Bosch, Juan J.Bittner, Rachel M.Salamon, JustinGómez Gutiérrez, Emilia, 1975-2016-07-082016-07-082016Bosch JJ, Bittner RM, Salomon J, Gómez E. A comparison of melody extraction methods based on source-filter modelling. Paper presented at: ISMIR 2016. 17th International Society for Music Information Retrieval Conference; 2016 Aug 7-11; New York, United States.http://hdl.handle.net/10230/27016This work explores the use of source-filter models for pitch/nsalience estimation and their combination with different/npitch tracking and voicing estimation methods for automatic/nmelody extraction. Source-filter models are used/nto create a mid-level representation of pitch that implicitly/nincorporates timbre information. The spectrogram of/na musical audio signal is modelled as the sum of the leading/nvoice (produced by human voice or pitched musical instruments)/nand accompaniment. The leading voice is then/nmodelled with a Smoothed Instantaneous Mixture Model/n(SIMM) based on a source-filter model. The main advantage/nof such a pitch salience function is that it enhances/nthe leading voice even without explicitly separating it from/nthe rest of the signal. We show that this is beneficial/nfor melody extraction, increasing pitch estimation accuracy/nand reducing octave errors in comparison with simpler/npitch salience functions. The adequate combination with/nvoicing detection techniques based on pitch contour characterisation/nleads to significant improvements over stateof-the-art/nmethods, for both vocal and instrumental music.application/pdfengLicensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Attribution: Juan J. Bosch, Rachel M. Bittner, Justin Salomon, Emilia Gómez. "A comparison of melody extraction methods based on source-filter modelling", 17th International Society for Music Information Retrieval Conference, 2016, New York, United States.A comparison of melody extraction methods based on source-filter modellinginfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccess