Biblio
] Filters: Author is Rafael Ramirez [Clear All Filters]
(2014). P300 Harmonies: A Brain-Computer Musical Interface.
International Computer Music Conference/Sound and Music Computing Conference. Abstract
(2013). A High-Throughput Auditory P300 Interface for Everyone.
12th European AAATE Conference. 478-482. Abstract
(2012). A Brain-Gaze Controlled Musical Interface.
Berlin BCI Workshop 2012 - Advances in Neurotechnology.
(2015). A PERCUSSIVE MUSICAL INTERFACE FOR A QUADRIPLEGIC PATIENT.
International Symposium on Performance Science 2015. 60-61.
(2015). Is an auditory P300-based Brain-Computer Musical Interface feasible?.
CMMR2015: International Workshop on BCMI.
(2013). Towards a Low Cost Mu-Rhythm Based BCI.
Fifth International Brain-Computer Interface Meeting 2013.
(2015). EEG Signal classification in a Brain-Computer Music Interface.
8th International Workshop on Machine Learning and Music. 28-30.
(2011). THE EYEHARP: AN EYE-TRACKING-BASED MUSICAL INSTRUMENT.
8th Sound and Music Computing Conference.
(2016). Digital Musical Instruments for People with Physical Disabilities.
Department of Information and Communication Technologies. 163.
(2016). The EyeHarp: A Gaze-Controlled Digital Musical Instrument.
Frontiers in Psychology . 7,
(2012). Temporal Control In the EyeHarp Gaze-Controlled Musical Interface.
New Interfaces for Musical Expression (NIME) 2012. Abstract
(2008). A Genetic Rule-based Expressive Performance Model for Jazz Saxophone.
Computer Music Journal. 32, 38-50. Abstract
(2009). A Framework for Performer Identification in Audio Recordings.
International Workshop on Machine Learning and Music - ECML-PKDD 09. Abstract
(2005). Modeling expressive music performance in jazz.
International Florida Artificial Intelligence Research Society Conference. Abstract
(2007). Identifying saxophonists from their playing styles.
30th AES Conference. Abstract
(2008). Performer Identification in Celtic Violin Recordings.
International Conference on Music Information Retrieval. Abstract
(2004). Understanding expressive transformations in saxophone jazz performances using inductive machine learning.
Sound and Music Computing Conference. Abstract
(2006). A Machine Learning Approach to Expressive Performance in Jazz Standards.
(, Ed.).Multimedia Data Mining and Knowledge Discovery. Abstract
(2003). Learning Sets of Musical Rules.
Abstract
(2006). Training a Classifier to Detect Instantaneous Musical Cognitive States.
International Conference on Music Perception and Cognition. Abstract
(2008). An fMRI Study on Attentive Music Listening.
The Neurosciences and Music. Abstract
(2005). Intra-note Features Prediction Model for Jazz Saxophone Performance.
International Computer Music Conference. Abstract
(2006). A Sequential Covering Evolutionary Algorithm for Expressive Music Performance.
Conference on Innovative Applications of Artificial Intelligence. Abstract
(2004). A machine learning approach to expressive performance in jazz standards.
ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. Abstract
