AutoRhythmGuitar: Computer-aided Composition for Rhythm Guitar in the Tab Space

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Exploring socioeconomic factors for the sustainability of electric guitar brands: focusing on traditional values and psychological attachment

The primary objective of this study was to conduct a comprehensive quantitative analysis to investigate the factors influencing the purchase of electric guitars. Building upon prior research related to the decision-making process behind electric guitar purchases, our research took a quantitative approach to shed light on this intricate process. We designed and tested six hypotheses, utilizing structural equation modeling to analyze a dataset consisting of 433 responses collected within the electric guitar community. The results of our study have uncovered intriguing insights into the factors that drive purchase intention among electric guitar enthusiasts. Notably, two out of the six variables examined, namely 'Brand' and 'Heritage Value,' were found to exert a significant impact on consumers' intentions to purchase electric guitars. This discovery carries profound implications for the industry. It is worth highlighting that electric guitars possess inherent features that can enhance a player's skill and convenience through cutting-edge digital technology. However, our findings reveal that players place a higher emphasis on the perceived heritage value and brand identity of electric guitars, which take precedence over their functional attributes when making guitar selection decisions. This preference for cultural and emotional aspects over utilitarian features is a significant revelation. In light of the current state of the electric guitar industry, which is experiencing a decline, our research suggests that emphasizing and promoting the heritage and brand values of electric guitars could prove instrumental in retaining existing customers and attracting new ones. This strategic shift could serve to revitalize the industry and counter the challenges posed by advancements in technology. In summary, our study reaffirms the importance of cultural and emotional elements in consumers' decisions regarding electric guitar purchases, underscoring the need for industry players to adapt and focus on these aspects to remain competitive in a changing market landscape

Proceedings of the 19th Sound and Music Computing Conference

Proceedings of the 19th Sound and Music Computing Conference - June 5-12, 2022 - Saint-Étienne (France). https://smc22.grame.f

Avaliação de um método de correlação para aplicação em um detector e classificador de acordes

Desenvolvimento de um sistema de identificação e classificação de frequências sonoras simultâneas (acordes) com aplicação voltada para o ramo musical baseado no coeficiente de correlação e em uma função linear de threshold. Utilizando o software MATLAB 2016a, são elaboradas funções que calculam a correlação entre um acorde e uma base de dados de notas individuais previamente gerada, contendo 36 notas gravadas de uma guitarra elétrica, utilizando uma interface de áudio para gravação em 96 kHz de amostragem, que é reduzida posteriormente para 48 kHz para fins de processamento. Todas as operações sobre os sinais são feitas no domínio frequência, utilizando a FFT (Fast Fourier Transform) para o tratamento dos sinais de áudio. São desenvolvidos dois tipos de seletores de notas a fim de fornecer a saída na forma de notas detectadas. No primeiro seletor, todas as notas consideradas detectadas são informadas na saída. No segundo seletor, dentre todos os valores de correlação, o sistema escolhe os 6 maiores valores para apontar como prováveis notas executadas no sinal de entrada. São realizados testes com 10 amostras de 20 acordes diferentes para caracterizar os classificadores quanto à sua taxa de acerto, falsos positivos e negativos. Também é feita análise da performance dos classificadores utilizando curvas ROC. De posse dos resultados finais, concluiu-se que o coeficiente de correlação pode ser considerado uma boa ferramenta para a comparação dos sinais na aplicação proposta. O primeiro seletor demonstrou melhor taxa de acerto do que o segundo seletor, por ser menos restritivo e informar todas as notas detectadas. As taxas de acerto máximas para o primeiro seletor variam de 0 a 100 % dependendo do acorde, enquanto as taxas do segundo variam de 0 a 66,6667% de acerto máximo. Foi mostrado que para acordes de tons diferentes e construídos de diferentes intervalos, a taxa de acerto dos testes variou de uma forma sem padrão específico. Todavia, a função utilizada como limiar de detecção para o classificador apresentou performance limitada para os dois seletores desenvolvidos, onde, na maioria dos casos, para altos valores de taxa de acerto, esta retorna alta taxa de falsos positivos e, para baixos valores de falsos positivos, esta obtém baixa taxa de verdadeiros positivos.Development of a system of detection and classification of simultaneous sound frequencies (chords) with application oriented to the musical field based on the correlation coefficient and a linear function for threshold. Using MATLAB 2016a, functions are developed to calculate the correlation between a chord and a previously generated individual notes database containing 36 recorded notes of an electric guitar using an audio interface, sampling at 96 kHz, which is subsequently reduced to 48 kHz for processing purposes. All operations on the signals are done in the frequency domain, using the FFT (Fast Fourier Transform) for the treatment of audio signals. Two types of note selectors are developed to provide output in the form of detected notes. In the first selector, all notes considered detected are reported on the output. In the second selector, of all correlation values, the system chooses the 6 largest values to point as probable notes executed on the input signal Tests are performed with 10 samples of 20 different chords to characterize the classifiers as to their hit rate, false positives and negatives. Also, the performance of the classifiers was analysed using ROC curve. With the final results, it was concluded that the correlation coefficient can be considered as a good tool for the comparison of the signals in the proposed application. The first selector showed a better hit rate than the second selector, because it was less restrictive, reporting all of the detected notes. The hit rates for the first selector range from 0 to 100 % depending on the chord, while the second hit rates vary from 0 to 66,6667 %. It was shown that for different tones and for different construction of chords, the hit rates vary without a specific pattern. However, the function used as the detection threshold for the classifier showed limited performance for the two developed selectors, where, in most cases, with high values of hit rate, it returns a high rate of false positives and with low values of false positives, it returns a low rate of true positives

The development of corpus-based computer assisted composition program and its application for instrumental music composition

In the last 20 years, we have seen the nourishing environment for the development of music software using a corpus of audio data expanding significantly, namely that synthesis techniques producing electronic sounds, and supportive tools for creative activities are the driving forces to the growth. Some software produces a sequence of sounds by means of synthesizing a chunk of source audio data retrieved from an audio database according to a rule. Since the matching of sources is processed according to their descriptive features extracted by FFT analysis, the quality of the result is significantly influenced by the outcomes of the Audio Analysis, Segmentation, and Decomposition. Also, the synthesis process often requires a considerable amount of sample data and this can become an obstacle to establish easy, inexpensive, and user-friendly applications on various kinds of devices. Therefore, it is crucial to consider how to treat the data and construct an efficient database for the synthesis. We aim to apply corpusbased synthesis techniques to develop a Computer Assisted Composition program, and to investigate the actual application of the program on ensemble pieces. The goal of this research is to apply the program to the instrumental music composition, refine its function, and search new avenues for innovative compositional method