From Pythagoras to Johann Sebastian Bach: An Exploration in the Development of Temperament and Tuning

Temperament and tuning are at the core of all music—they are the embodiment of the correlation of music and mathematics in every musical work. In examining the shift from Pythagorean tuning to well temperament, compositional style and philosophy governs not only the evolution musical genres, but also the evolution of temperament and tuning systems. The association of mathematics and temperament defines ratios and pitch relations in every branch of temperament. An analysis of J.S. Bach\u27s Well-Tempered Clavier and his use of temperament display the contrast of melodious thirds of meantone temperament and emotional tension of chords in well temperament. The mathematical beauty and complexity of tuning governs the musical center of the work; a composition may focus upon minute intervallic relationships or larger harmonic structure, depending upon the primary focus of the utilized system of temperament. Arguably, mathematical relationships have more influence upon musical beauty than the composed music alone. J.S. Bach\u27s preludes and fugues of the Well-Tempered Clavier prove the existence of liveliness and color in every possible key

Imaging time series for the classification of EMI discharge sources

In this work, we aim to classify a wider range of Electromagnetic Interference (EMI) discharge sources collected from new power plant sites across multiple assets. This engenders a more complex and challenging classification task. The study involves an investigation and development of new and improved feature extraction and data dimension reduction algorithms based on image processing techniques. The approach is to exploit the Gramian Angular Field technique to map the measured EMI time signals to an image, from which the significant information is extracted while removing redundancy. The image of each discharge type contains a unique fingerprint. Two feature reduction methods called the Local Binary Pattern (LBP) and the Local Phase Quantisation (LPQ) are then used within the mapped images. This provides feature vectors that can be implemented into a Random Forest (RF) classifier. The performance of a previous and the two new proposed methods, on the new database set, is compared in terms of classification accuracy, precision, recall, and F-measure. Results show that the new methods have a higher performance than the previous one, where LBP features achieve the best outcome

A computational framework for aesthetical navigation in musical search space

Paper presented at 3rd AISB symposium on computational creativity, AISB 2016, 4-6th April, Sheffield. Abstract. This article addresses aspects of an ongoing project in the generation of artificial Persian (-like) music. Liquid Persian Music software (LPM) is a cellular automata based audio generator. In this paper LPM is discussed from the view point of future potentials of algorithmic composition and creativity. Liquid Persian Music is a creative tool, enabling exploration of emergent audio through new dimensions of music composition. Various configurations of the system produce different voices which resemble musical motives in many respects. Aesthetical measurements are determined by Zipf’s law in an evolutionary environment. Arranging these voices together for producing a musical corpus can be considered as a search problem in the LPM outputs space of musical possibilities. On this account, the issues toward defining the search space for LPM is studied throughout this paper

Avatars and Lebensform: Kirchberg 2007

Several years ago, after a decade of experiments in the software industry, I returned to academia and found philosophy colleagues troubled by the term “virtual reality” — a term which enjoys wide usage in the ?eld of immersive computing but which raises hackles in post-metaphysical philosophers. Some vocabulary in this paper may create similar unease, so a warning may be in order. What makes sense to software engineers may for philosophers carry too much baggage. Words like “empathetic” or “empathic” may cause similar discomfort for those with an allergy to Romanticism. While these adjectives associated with poets like Wordsworth, the term “empathy” belongs equally to software designers and video-game artists who use it to describe the opposite of “?rst-person shooter” software. Empathic, as opposed to “shoot ‘em up” software, encourages the exchange of viewpoints beyond ?rst-person perspective and may even merge several perspectives. Rather than deepen a user’s ?rst-person point-of-view, empathic software offers a socializing experience, and in fact, is sometimes called “social” software, “Net 2.0,” or “computer supported cooperative work.

MIDI-VAE: Modeling Dynamics and Instrumentation of Music with Applications to Style Transfer

We introduce MIDI-VAE, a neural network model based on Variational Autoencoders that is capable of handling polyphonic music with multiple instrument tracks, as well as modeling the dynamics of music by incorporating note durations and velocities. We show that MIDI-VAE can perform style transfer on symbolic music by automatically changing pitches, dynamics and instruments of a music piece from, e.g., a Classical to a Jazz style. We evaluate the efficacy of the style transfer by training separate style validation classifiers. Our model can also interpolate between short pieces of music, produce medleys and create mixtures of entire songs. The interpolations smoothly change pitches, dynamics and instrumentation to create a harmonic bridge between two music pieces. To the best of our knowledge, this work represents the first successful attempt at applying neural style transfer to complete musical compositions.Comment: Paper accepted at the 19th International Society for Music Information Retrieval Conference, ISMIR 2018, Paris, Franc