PLXTRM: Prediction-Led eXtended-guitar Tool for Real-time Music applications and live performance

References

• Bressan, F. (2014). The preservation and restoration of systems for automatic music performance. Canazza, S., & Rodà, A. eds. Proceedings of the 1st International Workshop on Computer and Robotic Systems for Automatic Music Performance (SAMP14) in conjunction with the 13th International Conference on Intelligent Autonomous Systems (IAS) (pp. 1–8). Venezia (Italy).
   Google Scholar
• Craenen. (2012). Instruments for new ears. World new music magazine, 22:90–99.
   Google Scholar
• Essl, G., & O’modhrain, S. (2006). An enactive approach to the design of new tangible musical instruments. Organised Sound, 11, 285–296.
   Google Scholar
• Fala, J., Keshap, A., Doerning, M., & Barbeau, J. (1991). Note sensing in m.i.d.i. guitars and the like. US Patent 5,033,353.
   Google Scholar
• Fernando, C., & Sojakka, S. (2003). Pattern recognition in a bucket. Advances in artificial life (pp. 588–597). Berlin: Springer
   Google Scholar
• French, R. M. (2008). Engineering the guitar: theory and practice. Berlin:Springer Science & Business Media.
   Google Scholar
• Godøy, R. I., & Leman, M. (2010). Musical gestures: Sound, movement, and meaning. New York: Routledge.
   Google Scholar
• Holm, P., & Williams, B. (2014). Electronic guitar pick and method. US Patent App. 14/092,709.
   Google Scholar
• Hoppe, D., Brandmeyer, A., Sadakata, M., Timmers, R., & Desain, P. (2006). The effect of real-time visual feedback on the training of expressive performance skills. 9th International Conference on Music Perception and Cognition (ICMPC9) The Society for Music Perception & Cognition (SMPC) and European Society for the Cognitive Sciences of Music (ESCOM), Bologna, Italy.
   Google Scholar
• Howard, D. M., Welch, G. F., Brereton, J., Himonides, E., DeCosta, M., Williams, J., & Howard, A. W. (2004). Winsingad: A real-time display for the singing studio*. Logopedics Phonatrics Vocology, 29, 135–144.
   PubMedGoogle Scholar
• Keebler, J. R., Wiltshire, T. J., Smith, D. C., Fiore, S. M., & Bedwell, J. S. (2014). Shifting the paradigm of music instruction: implications of embodiment stemming from an augmented reality guitar learning system. Frontiers in psychology, 5:1–18.
   PubMed Web of Science ®Google Scholar
• Kessous, L., Castet, J., & Arfib, D. (2006). ‘gxtar’, an interface using guitar techniques. Proceedings of the 2006 conference on New interfaces for musical expression (pp. 192–195). , Paris, France: IRCAM–Centre Pompidou.
   Google Scholar
• Lähdeoja, O. (2015). An augmented guitar with active acoustics. SMC Proceedings of the Sound and Music Computing Conference. Retrieved from http://smcnetwork.org/node/1888
   Google Scholar
• Lähdeoja, O., Wanderley, M., & Malloch, J. (2009). Instrument augmentation using ancillary gestures for subtle sonic effects. Proceedings of the SMC 2009–6th Sound and Music Computing Conference (pp. 327–330). Porto (Portugal).
   Google Scholar
• Larger, L., Soriano, M. C., Brunner, D., Appeltant, L., Gutiérrez, J. M., Pesquera, L., Mirasso, C. R., & Fischer, I. (2012). Photonic information processing beyond turing: an optoelectronic implementation of reservoir computing. Optics Express, 20, 3241–3249.
   PubMed Web of Science ®Google Scholar
• Larsen, J. V., Overholt, D., & Moeslund, T. B. (2013). The actuated guitar: A platform enabling alternative interaction methods. SMC Proceedings of the Sound and Music Computing Conference (pp. 235–238). Logos Verlag Berlin, Stockholm, Sweden..
   Google Scholar
• Leman, M. (2007). Embodied music cognition and mediation technology. Cambridge, MA: The MIT Press.
   Google Scholar
• Leman, M. (2016). The expressive moment: how music interaction shapes empowerment. Cambridge, MA: The MIT Press.
   Google Scholar
• Lukoševičius, M. & Jaeger, H. (2009). Reservoir computing approaches to recurrent neural network training. Computer Science Review, 3, 127–149.
   Google Scholar
• Maes, P.-J., Leman, M., Palmer, C., & Wanderley, M. M. (2014). Action-based effects on music perception. Frontiers in Psychology, 4, 1–14.
   Web of Science ®Google Scholar
• Maes, P.-J., Nijs, L., & Leman, M. (2015). A conceptual framework for music-based interaction systems. In R. Bader (Ed.), Springer Handbook in Systematic Musicology. Berlin Heidelberg: Springer.
   Google Scholar
• McPherson, A. P., Jack, R. H., & Moro, G. (2016). Action-sound latency: Are our tools fast enough?. Proceedings of the international conference on new interfaces for musical expression (NIME 2016) (Vol. 16, pp. 2220–4806). Queensland Conservatorium Griffith University. 20--25, Brisbane (Australia).
   Google Scholar
• Miranda, E. R., & Wanderley, M. M. (2006). New digital musical instruments: control and interaction beyond the keyboard (Vol. 21). Middleton, WI: AR Editions Inc.
   Google Scholar
• Moens, B., & Leman, M. (2015). Alignment strategies for the entrainment of music and movement rhythms. Annals of the New York Academy of Sciences, 1337, 86–93.
   PubMed Web of Science ®Google Scholar
• Moens, B., Muller, C., van Noorden, L., Franěk, M., Celie, B., Boone, J., Bourgois, J., & Leman, M. (2014). Encouraging spontaneous synchronisation with D-Jogger, an adaptive music player that aligns movement and music. PLoS ONE, 9(12), 1–40.
   Web of Science ®Google Scholar
• Moens, B., van Noorden, L., Leman, M., Nordahl, R., Fontana, F., & Brewster, S. (2010). D-jogger: A multimodal music interface for music selection based on user step frequency. Proceedings of the Haptic and Audio Interaction Design Conference (pp. 2). Barcelona: Universidad Pompeu Fabra
   Google Scholar
• Oda, R., Finkelstein, A., & Fiebrink, R. (2013). Towards note-level prediction for networked music performance. NIME. 2, 94-97.
   Google Scholar
• Pakarinen, J., & Puputti, T. (2008). Slide guitar synthesizer with gestural control. Proceedings of 8th International Conference on New Interfaces for Musical Expression (NIME08) (pp. 5-7), Genoa, Italy.
   Google Scholar
• Paquot, Y., Duport, F., Smerieri, A., Dambre, J., Schrauwen, B., Haelterman, M., & Massar, S. (2012). Optoelectronic reservoir computing. Scientific Reports, 2, 1–15.
   Google Scholar
• Perng, C., Smith, J., & Rossing, T. (2011). Harpsichord sound synthesis using a physical plectrum model interfaced with the digital waveguide. International Conference on Digital Audio Effects (DAFx-11), IRCAM – Centre Pompidou, Paris, France .
   Google Scholar
• Polson, R. (1982). Digital high speed guitar synthesizer. US Patent 4,336,734.
   Google Scholar
• Schrauwen, B., Verstraeten, D., & Van Campenhout, J. (2007). An overview of reservoir computing: Theory, applications and implementations. Proceedings of the 15th European symposium on artificial neural networks. Bruges, Belgium: Citeseer.
   Google Scholar
• Thorpe, C. W. (2002). Visual feedback of acoustic voice features in voice training. Esitelmä pidetty Australian kansainvälisessä puhetieteen ja-teknologian konferenssissa. Retrieved from https://www.singandsee.com/articles/SST2002-Thorpe098.pdf
   Google Scholar
• Trail, S., Dean, M., Odowichuk, G., Tavares, T. F., Driessen, P. F., Schloss, W. A., & Tzanetakis, G. (2012). Non-invasive sensing and gesture control for pitched percussion hyper-instruments using the kinect. NIME. Retrieved from http://vhosts.eecs.umich.edu/nime2012/Proceedings/NIME2012WebProceedings.html
   Google Scholar
• Vanegas, R. (2007). The midi pick: Trigger serial data, samples, and midi from a guitar pick. Proceedings of the 7th International Conference on New Interfaces for Musical Expression (pp. 330–332). New York: ACM.
   Google Scholar
• von dem Knesebeck, A., & Zölzer, U. (2010). Comparison of pitch trackers for real-time guitar effects. Proceedings of the 13th International Conference on Digital Audio Effects (DAFx) (pp. 266–269). Graz.
   Google Scholar
• Welch, G. F., Howard, D. M., Himonides, E., & Brereton, J. (2005). Real-time feedback in the singing studio: An innovatory action-research project using new voice technology. Music Education Research, 7, 225–249.
   Google Scholar
• Xiao, X., Tome, B., & Ishii, H. (2014). Andante: Walking figures on the piano keyboard to visualize musical motion. In B. Caramiaux, K. Tahiroglu, R. Fiebrink, & A. Tanaka (Eds.), Proceedings of the 14th International Conference on New Interfaces for Musical Expression. Goldsmiths: University of London.
   Google Scholar