Biblio

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Gulati, S. (2012).  A Tonic Identification Approach for Indian Art Music. Abstract
Gulati, S., Salamon J., & Serra X. (2012).  A Two-stage Approach for Tonic Identification in Indian Art Music. 2nd CompMusic Workshop. Abstract
application/pdf icon23-Sankalp-Gulati-2nd-CompMusic-Workshop-2012.pdf
Guerra, E. (1998).  VowSynth A Synthesizer of Vowel Sounds Based on Additive Synthesis. International Conference on Digital Audio Effects (DAFX). Abstract
Guerra, E. (1998).  Disseny i implementació d`un sintetitzador de veu cantada. Abstract
Guaus, E. (2004).  New approaches for rhythmic description of audio signals. Abstract
Guaus, E., & Herrera P. (2006).  Music Genre Categorization in Humans and Machines. 121th AES Convention. Abstract
Guaus, E., & Batlle E. (2003).  Visualization of metre and other rhythm features. International Symposium on Signal Processing and Information Technology. Abstract
Guaus, E., Bonada J., Pérez A., Maestre E., & Blaauw M. (2007).  Measuring the bow pressing force in a real violin performance. International Symposium on Musical Acoustics. Abstract
Guaus, E., & Gómez E. (2005).  Storage and Retrieval of relevant information from music master classes. 36th conference of the International Association of Sound and Audiovisual Archives (IASA). Abstract
Guaus, E., & Herrera P. (2005).  The Rhythm Transform: Towards A Generic Rhythm Description. International Computer Music Conference. 1311. Abstract
Guaus, E., & Herrera P. (2007).  A basic system for music genre classification. International Conference on Music Information Retrieval. Abstract
Guaus, E., & Herrera P. (2006).  Towards better automatic genre classifiers by means of understanding human decisions on genre discrimination. International Conference on Music Perception and Cognition. 326-327. Abstract
Guaus, E., & Batlle E. (2004).  A non-linear rhythm-based style classifcation for Broadcast Speech-Music Discrimination. 116th AES Convention. Abstract
Guaus, E. (2009).  Audio content processing for automatic music genre classification: descriptors, databases, and classifiers. Department of Information and Communication Technologies. Abstract
Guaus, E., Bonada J., Maestre E., Pérez A., & Blaauw M. (2009).  Calibration method to measure accurate bow force for real violin performances . (Scavone, G., Ed.).International Computer Music Conference. 251-254. Abstract
Guastavino, C., Gómez F., Toussaint G., Marandola F., & Gómez E. (2009).  Measuring Similarity between Flamenco Rhythmic Patterns. Journal of New Music Research. 38(2), 129-138. Abstract
application/pdf iconGuastavinoEtAlJNMR2009.pdf
Grachten, M., Marxer R., Hazan A., & Purwins H. (2007).  Attention as musical interplay of bottom-up accents and expectation. GOSPEL Workshop. Abstract
Grachten, M. (2006).  Expressivity-aware Tempo Transformations of Music Performances Using Case Based Reasoning. Abstract
Gouyon, F., & Dixon S. (2005).  A review of automatic rhythm description systems. Computer Music Journal. 29, Abstract
Gouyon, F., Widmer G., Serra X., & Flexer A. (2006).  Acoustic Cues to Beat Induction. A Machine Learning Perspective. Music Percepcion. UCPress. 24, 177-188. Abstract
Gouyon, F., Wack N., & Dixon S. (2004).  An open source tool for semi-automatic rhythmic annotation. Abstract
Gouyon, F., & Dixon S. (2005).  Influence of input features in perceptual tempo induction. Abstract
Gouyon, F., & Meudic B. (2003).  Towards Rhythmic Content Processing of Musical Signals Fostering Complementary Approaches. Journal of New Music Research. 32, Abstract
Gouyon, F., Klapuri A., Dixon S., Alonso M., Tzanetakis G., Uhle C., et al. (2006).  An experimental comparison of audio tempo induction algorithms. IEEE Transactions on Speech and Audio Processing. 14, Abstract
Gouyon, F., Widmer G., & Serra X. (2005).  Acoustic Cues to Beat Induction A Machine Learning Perspective. 10th Rhythm Perception and Production Workshop. 24(2), 177-188. Abstract
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