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- Multi Pitch Estimation of Piano Music using Cartesian Genetic Programming with Spectral Harmonic MaskPublication . Miragaia, Rolando; Reis, Gustavo; Fernandéz de Vega, Francisco; Chávez, FranciscoPiano notes recognition, or pitch estimation of piano notes has been a popular research topic for many years, and is still investigated nowadays. It is a fundamental task during the process of automatic music transcription (extracting the musical score from an acoustic signal). We take advantage of Cartesian Genetic Programming (CGP) to evolve mathematical functions that act as independent classifiers for piano notes. These classifiers are then used to identify the presence of piano notes in polyphonic audio signals. This paper describes our technique and the latest improvements made in our research. The main feature is the introduction of spectral harmonic masks in the binarization process for measuring the fitness values that has allowed to improve the classification rate: 10% in the F-measure mean result. Our system architecture is also described to show the feasibility of its parallelization, which will reduce the computing time.
- Cooperative and decomposable approaches on royal road functionsPublication . Reis, Gustavo; Fernandéz, Francisco; Olague, Gustavo
- Cartesian genetic programming applied to pitch estimation of piano notesPublication . Inacio, Tiago; Miragaia, Rolando; Reis, Gustavo; Grilo, Carlos; Fernandez, FranciscoPitch Estimation, also known as Fundamental Frequency (F0) estimation, has been a popular research topic for many years, and is still investigated nowadays. This paper presents a novel approach to the problem of Pitch Estimation, using Cartesian Genetic Programming (CGP). We take advantage of evolutionary algorithms, in particular CGP, to evolve mathematical functions that act as classifiers. These classifiers are used to identify piano notes' pitches in an audio signal. For a first approach, the obtained results are very promising: our error rate outperforms two of three state-of-the-art pitch estimators.
- CGP4Matlab - A Cartesian Genetic Programming MATLAB Toolbox for Audio and Image ProcessingPublication . Miragaia, Rolando; Jorge dos Reis, Gustavo Miguel; Fernandéz, Francisco; Inácio, Tiago; Grilo, CarlosThis paper presents and describes CGP4Matlab, a powerful toolbox that allows to run Cartesian Genetic Programming within MATLAB. This toolbox is particularly suited for signal processing and image processing problems. The implementation of CGP4Matlab, which can be freely downloaded, is described. Some encouraging results on the problem of pitch estimation of musical piano notes achieved using this toolbox are also presented. Pitch estimation of audio signals is a very hard problem with still no generic and robust solution found. Due to the highly flexibility of CGP4Matlab, we managed to apply a new cartesian genetic programming based approach to the problem of pitch estimation. The obtained results are comparable with the state of the art algorithms. © Springer International Publishing AG, part of Springer Nature 2018.
- AMIGA - An Interactive Musical Environment for GerontechnologyPublication . Reis, Lee Scott; Reis, Gustavo; Barroso, João; Pereira, AntónioBenefits provided by music in humans have been reinforced through several studies, mainly by active participation in musical therapy sessons, with surprising results in physical and psychological rehabilitation. However, all the previous implemented approaches require specialized hardware to function and complex configurations to set-up. We define a computational system focused on the elderly to allow musical expressiveness through motion, solely using the resources available in an ordinary home computer. To evaluate our approach, we developed a prototype and piloted acceptance tests on several senior citizens, with an average age of eighty-three. Our experiments showed high levels of interest from the senior citizens, denoting positive capabilities of well-being and life quality enrichment. The performed experiments have also shown that an ordinary computer is capable of performing the proposed methodology, without any restriction.