Biblio

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Marinescu, M., & Ramirez R. (2008).  Expressive Performance in the Human Tenor Voice. Sound and Music Computing Conference. Abstract
Marley, W. (2013).  Processing an Instrumental Gesture in the Reactable as a Method of Computer Improvisation. Abstract
application/pdf iconLiam-Marley-Master-Thesis-2013.pdf
Marques, G., Lopes M., Sordo M., Langlois T., & Gouyon F. (2010).  Additional Evidence That Common Low-level Features Of Individual Audio Frames Are Not Representative Of Music Genre. 7th Sound and Music Computing Conference, 2010, Barcelona, Spain. Abstract
application/pdf icon20.pdf
Marques, G., Langlois T., Gouyon F., Lopes M., & Sordo M. (2011).  Short-term feature space and Music Genre Classification. Journal of New Music Research. 40(2), 127-137. Abstract
Marrero, M., & Urbano J. (2015).  Information Extraction Grammars. 37th European Conference on Information Retrieval. 265-270. Abstract
application/pdf icon056-information-extraction-grammars.pdf
Martel, H., & Miron M. (2017).  Data augmentation for deep learning source separation of HipHop songs. 10th International Workshop on Machine Learning and Music. Abstract
Marti, F., Lopez D., & Resina E. (1998).  Vocem An Application for Real-Time Granular Synthesis. Abstract
Martín, D. (2009).  Automatic accompaniment for improvised music. Abstract
Martínez, E., Celma Ò., Sordo M., De Jong, B, & Serra X. (2009).  Extending the folksonomies of freesound.org using content-based audio analysis. Sound and Music Computing Conference. Abstract
Martínez, E., Adiloglu K., Anniés R., Purwins H., & Obermayer K. (2007).  Perceptual Representations for Classification of Everyday Sounds. Audio Mostly . Abstract
Martínez, E. (2008).  Issues on Retrieval of Sound Effects in Large Collaborative Databases.
Martinez, A. (2004).  Técnicas de procesado de lenguaje natural para gestión de contenidos de audio análisis de letras y etiquetado.
Martinez, M. S. (2019).  MORPHEX - A Spectral Morphing Synthesizer. Abstract
Martorell, A. (2013).  Modelling tonal context dynamics by temporal multi-scale analysis. Department of Information and Communication Technologies. 153. Abstract
Martorell, A., & Gómez E. (2014).  Hierarchical multi-scale set-class analysis. Journal of Mathematics and Music: Mathematical and Computational Approaches to Music Theory, Analysis, Composition and Performance. 1-14. Abstract
Martorell, A. (2014).  Set-class surface analysis: a hierarchical multi-scale approach. 7th Workshop on Machine Learning and Music (MML 2014). Abstract
application/pdf iconSet-class surface analysis. A hierarchical multi-scale approach.pdf
Martorell, A. (2014).  Systematic set-class surface analysis: a hierarchical multi-scale approach. 8th European Music Analysis Conference (EuroMAC). Abstract
Martorell, A. (2009).  Tonal stability modeling from audio chroma features. Abstract
Martorell, A., & Gómez E. (2014).  Systematic multi-scale set-class analysis. 15th International Society for Music Information Retrieval (ISMIR) Conference. Abstract
application/pdf iconSystematic multi-scale set-class analysis.pdf
Martorell, A., & Gómez E. (2015).  Contextual set-class analysis. (D. Meredith, Ed.).Computational Music Analysis. 81-110. Abstract
application/pdf iconpreprint version
Martorell, A., & Gómez E. (2011).  Two-Dimensional Visual Inspection of Pitch-Space, Many Time-Scales and Tonal Uncertainty Over Time. 3rd International Conference on Mathematics and Computation in Music (MCM 2011). Abstract
application/pdf iconmcm2011-2.pdf
Martorell, A. (2015).  Digital encodings of early music: usability factors for computational analysis. International Workshop on Musicology and Informatics in Dialogue. Abstract
Martorell, A., Toiviainen P., & Gómez E. (2012).  Temporal multi-scale considerations in the modeling of tonal cognition from continuous rating experiments. International Conference on Music Perception and Cognition. Abstract
application/pdf iconTemporal multi-scale considerations in the modeling of tonal cognition from continuous rating experiments.pdf
Marxer, R., & Janer J. (2012).  A Tikhonov Regularization Method For Spectrum Decomposition In Low Latency Audio Source Separation. International Conference on Acoustics, Speech, and Signal Processing (ICASSP). 277-280.
application/pdf icon0000277.pdf
Marxer, R., & Purwins H. (2010).  Unsupervised Incremental Learning and Prediction of Audio Signals. International Symposium on Music Acoustics. Abstract
application/pdf iconMarxerPurwinsUnsupervisedIncrementalPredictionAudioISMA2010.pdf
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