Productive Misreading in Intermedia Art: Four Approaches by a Musician

This discussion examines the evolution and lessons of four artistic performance works that engage with text and imagery with the mindset of a composer, rather than as an author or visual artist. The works involve computer music, improvisation, video art, generative art techniques, and challenging aesthetics. An analytical discussion reveals that different forms and mechanisms of reading are manifest in the artworks, and reflections upon these elucidate the intermedial nature of reading and the productive, expressive potential of interfering with these processes

Machine learning research that matters for music creation : a case study

Research applying machine learning to music modeling and generation typically proposes model architectures, training methods and datasets, and gauges system performance using quantitative measures like sequence likelihoods and/or qualitative listening tests. Rarely does such work explicitly question and analyse its usefulness for and impact on real-world practitioners, and then build on those outcomes to inform the development and application of machine learning. This article attempts to do these things for machine learning applied to music creation. Together with practitioners, we develop and use several applications of machine learning for music creation, and present a public concert of the results. We reflect on the entire experience to arrive at several ways of advancing these and similar applications of machine learning to music creation.QC 20180827</p

HReMAS: Hybrid Real-time Musical Alignment System

[EN] This paper presents a real-time audio-to-score alignment system for musical applications. The aim of these systems is to synchronize a live musical performance with its symbolic representation in a music sheet. We have used as a base our previous real-time alignment system by enhancing it with a traceback stage, a stage used in offline alignment to improve the accuracy of the aligned note. This stage introduces some delay, what forces to assume a trade-off between output delay and alignment accuracy that must be considered in the design of this type of hybrid techniques. We have also improved our former system to execute faster in order to minimize this delay. Other interesting improvements, like identification of silence frames, have also been incorporated to our proposed system.This work has been supported by the "Ministerio de Economia y Competitividad" of Spain and FEDER under Projects TEC2015-67387-C4-{1,2,3}-R.Cabañas-Molero, P.; Cortina-Parajón, R.; Combarro, EF.; Alonso-Jordá, P.; Bris-Peñalver, FJ. (2019). HReMAS: Hybrid Real-time Musical Alignment System. The Journal of Supercomputing. 75(3):1001-1013. https://doi.org/10.1007/s11227-018-2265-1S10011013753Alonso P, Cortina R, Rodríguez-Serrano FJ, Vera-Candeas P, Alonso-González M, Ranilla J (2017) Parallel online time warping for real-time audio-to-score alignment in multi-core systems. J Supercomput 73(1):126–138Alonso P, Vera-Candeas P, Cortina R, Ranilla J (2017) An efficient musical accompaniment parallel system for mobile devices. J Supercomput 73(1):343–353Arzt A (2016) Flexible and robust music tracking. Ph.D. thesis, Johannes Kepler University Linz, Linz, ÖsterreichArzt A, Widmer G, Dixon S (2008) Automatic page turning for musicians via real-time machine listening. In: Proceedings of the 18th European Conference on Artificial Intelligence (ECAI), Amsterdam, pp 241–245Carabias-Orti J, Rodríguez-Serrano F, Vera-Candeas P, Ruiz-Reyes N, Cañadas-Quesada F (2015) An audio to score alignment framework using spectral factorization and dynamic time warping. In: Proceedings of ISMIR, pp 742–748Cont A (2006) Realtime audio to score alignment for polyphonic music instruments, using sparse non-negative constraints and hierarchical HMMs. In: 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings, vol 5. pp V–VCont A, Schwarz D, Schnell N, Raphael C (2007) Evaluation of real-time audio-to-score alignment. In: International Symposium on Music Information Retrieval (ISMIR), ViennaDannenberg RB, Raphael C (2006) Music score alignment and computer accompaniment. Commun ACM 49(8):38–43Devaney J, Ellis D (2009) Handling asynchrony in audio-score alignment. In: Proceedings of the International Computer Music Conference Computer Music Association. pp 29–32Dixon S (2005) An on-line time warping algorithm for tracking musical performances. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI). pp 1727–1728Duan Z, Pardo B (2011) Soundprism: an online system for score-informed source separation of music audio. IEEE J Sel Top Signal Process 5(6):1205–1215Ewert S, Muller M, Grosche P (2009) High resolution audio synchronization using chroma onset features. In: IEEE International Conference on Acoustics, Speech and Signal Processing, 2009 (ICASSP 2009). pp 1869–1872Hu N, Dannenberg R, Tzanetakis G (2003) Polyphonic audio matching and alignment for music retrieval. In: 2003 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. pp 185–188Kaprykowsky H, Rodet X (2006) Globally optimal short-time dynamic time warping, application to score to audio alignment. In: Proceedings of the International Conference on Acoustics, Speech and Signal Processing, vol 5. pp. V–VLi B, Duan Z (2016) An approach to score following for piano performances with the sustained effect. IEEE/ACM Trans Audio Speech Lang Process 24(12):2425–2438Miron M, Carabias-Orti JJ, Bosch JJ, Gómez E, Janer J (2016) Score-informed source separation for multichannel orchestral recordings. J Electr Comput Eng 2016(8363507):1–19Muñoz-Montoro A, Cabañas-Molero P, Bris-Peñalver F, Combarro E, Cortina R, Alonso P (2017) Discovering the composition of audio files by audio-to-midi alignment. In: Proceedings of the 17th International Conference on Computational and Mathematical Methods in Science and Engineering. pp 1522–1529Orio N, Schwarz D (2001) Alignment of monophonic and polyphonic music to a score. In: Proceedings of the International Computer Music Conference (ICMC), pp 155–158Pätynen J, Pulkki V, Lokki T (2008) Anechoic recording system for symphony orchestra. Acta Acust United Acust 94(6):856–865Raphael C (2010) Music plus one and machine learning. In: Proceedings of the 27th International Conference on Machine Learning (ICML), pp 21–28Rodriguez-Serrano FJ, Carabias-Orti JJ, Vera-Candeas P, Martinez-Munoz D (2016) Tempo driven audio-to-score alignment using spectral decomposition and online dynamic time warping. ACM Trans Intell Syst Technol 8(2):22:1–22:2

Partiture: An Interoperable Music Stand Application for Mobile Devices

Peaaegu kõik saavutused tänapäeval taanduvad meeskonnatööle ja ühistegevusele. Erandiks ei ole ka muusika loomine ja esitamine. Heliloojad, luuletajad, seadete autorid, interpreedid, kollektiivid, dirigendid, koormeistrid, muusikaõpetajad – kõigi panused lõikuvad mingil tasandil teiste panustega. Leidub palju programme ja tööriistu, mis näiteks abistavad heliloojaid komponeerimisel, seadjaid seade loomisel, õpilasi mingi instrumendi õppimisel, jne. Siiski on reaalajas muusika-alast kaastööd võimaldavate vahendite hulk praktiliselt olematu. Dirigendid, muusikaõpetajad jätkuvalt edastavad kontekstiga seotud märkusi oma juhendatavatele suuliselt, mis tihtipeale põhjustab arusaamatusi ja informatsiooni kadu. Käesoleva töö eesmärgiks on välja töötada omavahel ühenduses olevate koostöövõimeliste noodipultide kontseptsioon, mis võiks muuta muusikute omavahelist suhtlemist tõhusamaks jagatud noodilehe keeramiste, märkuste kui ka tagasivõtu kohtade määramisel kiirelt ja üheseltmõistetavalt, kasutades selleks spetsiaalseid lokaalselt ülesseatud ajutisi traadita võrke. Tegemist on vastava tarkvarasüsteemi (Partiture) arendamise esimese etapiga.Almost every accomplishment can be retreated as an effort of teamwork and collaboration today – so can be creating and performing music. Composers, lyricists, arrangers, inter-preters, collectives, conductors, choirmasters, music teachers and students – all their con-tribution intersects at some level. There are many tools and programs available, which assist for example composers in creating the artwork, arrangers in modifying it for con-crete collective types, students in learning to play some instruments, etc. However, the circle of real-time collaboration supporting means is practically non-existent. Conductors, music teachers still do communicate all the context related notices to their mentees ver-bally, which often causes misunderstandings and information loss. This thesis presents the concept for interconnected interoperable music stand applications, which can enhance the cooperation between the musicians in the form of sharing page turns during performing, creating/sharing remarks and comments during practice sessions as well as locating retake positions fast and unambiguously, working over the air using ad-hoc based temporary networks. It is the introduction into the first phase of developing the corresponding soft-ware system (Partiture)

Real-Time Audio-to-Score Alignment of Music Performances Containing Errors and Arbitrary Repeats and Skips

This paper discusses real-time alignment of audio signals of music performance to the corresponding score (a.k.a. score following) which can handle tempo changes, errors and arbitrary repeats and/or skips (repeats/skips) in performances. This type of score following is particularly useful in automatic accompaniment for practices and rehearsals, where errors and repeats/skips are often made. Simple extensions of the algorithms previously proposed in the literature are not applicable in these situations for scores of practical length due to the problem of large computational complexity. To cope with this problem, we present two hidden Markov models of monophonic performance with errors and arbitrary repeats/skips, and derive efficient score-following algorithms with an assumption that the prior probability distributions of score positions before and after repeats/skips are independent from each other. We confirmed real-time operation of the algorithms with music scores of practical length (around 10000 notes) on a modern laptop and their tracking ability to the input performance within 0.7 s on average after repeats/skips in clarinet performance data. Further improvements and extension for polyphonic signals are also discussed.Comment: 12 pages, 8 figures, version accepted in IEEE/ACM Transactions on Audio, Speech, and Language Processin

Combining Score and Filter Based Models to Predict Tempo Fluctuations in Expressive Music Performances

(Abstract to follow