Biblio

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Neuschmied, H., Mayer H., & Batlle E. (2001).  Identification of Audio Titles on Internet. Abstract
Gong, R., & Serra X. (2017).  Identification of potential Music Information Retrieval technologies for computer-aided jingju singing training. The 5th China Conference on Sound and Music Technology - Chinese Traditional Music Technology Session. Abstract
Serrà, J. (2011).  Identification of versions of the same musical composition by processing audio descriptions. Department of Information and Communication Technologies. 154. Abstract
Ramirez, R., Maestre E., & Pertusa A. (2007).  Identifying saxophonists from their playing styles. 30th AES Conference. Abstract
Janer, J., Gómez E., Martorell A., Miron M., & de Wit B. (2016).  Immersive Orchestras: audio processing for orchestral music VR content. VSGAMES 2016 - 8th International Conference on Virtual Worlds and Games for Serious Applications. Abstract
Mealla, S., Väljamäe A., & Jordà S. (2011).  Implicit Interaction in Collaborative Music Performances. FutureBNCI. 1.
application/pdf iconFutureBNCI-RAVE11-submission.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).
Bencina, R., Kaltenbrunner M., & Jordà S. (2005).  Improved Topological Fiducial Tracking in the reacTIVision System. Abstract
Bonada, J., Blaauw M., & Loscos A. (2006).  Improvements to a Sample-Concatenation Based Singing Voice Synthesizer. Abstract
Kroher, N., & Gómez E. (2014).  Improving accompanied Flamenco singing voice transcription by combining vocal detection and predominant melody extraction.. International Computer Music Conference/Sound and Music Computing Conference. Abstract
application/pdf iconCameraReady_VoicingDetection.pdf
Parekh, S. (2015).  Improving Audio Retrieval through Content and Metadata Categorization. Abstract
application/pdf iconSanjeel-Parekh-Master-thesis-2015.pdf
Parekh, S., Font F., & Serra X. (2016).  Improving Audio Retrieval through Loudness Profile Categorization. 2016 IEEE International Symposium on Multimedia. 565-568. Abstract
application/pdf iconpostprint version
Jewalikar, V. (2013).  Improving automatic phonetic segmentation for creating singing voice synthesizer corpora. Abstract
Zapata, J. R., & Gómez E. (2012).  Improving Beat Tracking in the presence of highly predominant vocals using source separation techniques: Preliminary study. The 9th International Symposium on Computer Music Modeling and Retrieval (CMMR) . 583-590.
application/pdf iconBeatracking_with_source_separation_Jose_Zapata.pdf
Serrà, J., Gómez E., & Herrera P. (2008).  Improving binary similarity and local alignment for cover song detection. Music Information Retrieval Evaluation eXchange (MIREX) extended abstract. Abstract
Gulati, S., Serrà J., & Serra X. (2015).  Improving Melodic Similarity in Indian Art Music Using culture-Specific Melodic Characteristics. International Society for Music Information Retrieval Conference. 680-686. Abstract
application/pdf iconPoster
Miron, M., Carabias-Orti J. J., & Janer J. (2015).  Improving score-informed source separation for classical music through note refinement. 16th International Society for Music Information Retrieval (ISMIR) Conference. Abstract
application/pdf iconImproving score-informed source separation for classical music through note refinement.pdf
Vaquero, C. (2012).  Improving the description of instrumental sounds by using ontologies and automatic content analysis. Abstract
application/pdf iconCarlos-Vaquero-Master-Thesis-2012.pdf
Jordà, S. (2001).  Improvising with Computers A Personal Survey (1989-2001). Abstract
Jordà, S. (2002).  Improvising with Computers A Personal Survey (1989-2001). Journal of New Music Research. 31, pp 1-10. 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
Unal, E., Bozkurt B., & Karaosmanoglu K. M. (2012).  Incorporating Features of Distribution and Progression for Automatic Makam Classification. 2nd CompMusic Workshop.
application/pdf icon2012_1_CMW_Unal_etAl.pdf
Laurier, C., Meyers O., Serrà J., Blech M., Herrera P., & Serra X. (2010).  Indexing Music by Mood: Design and Integration of an Automatic Content-based Annotator. Multimedia Tools and Applications. 48(1), 161-184. Abstract
Marchini, M., Ramirez R., Papiotis P., & Maestre E. (2013).  Inducing rules of ensemble music performance: a machine learning approach. 3rd international conference on Music & Emotion, Jyväskylä.
Ramirez, R. (2004).  Inductive Logic Programming and Music.
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