The music style classification technology can add style tags to music based on the content. When it comes to researching and implementing aspects like efficient organization, recruitment, and music ...resource recommendations, it is critical. Traditional music style classification methods use a wide range of acoustic characteristics. The design of characteristics necessitates musical knowledge and the characteristics of various classification tasks are not always consistent. The rapid development of neural networks and big data technology has provided a new way to better solve the problem of music-style classification. This paper proposes a novel method based on music extraction and deep neural networks to address the problem of low accuracy in traditional methods. The music style classification algorithm extracts two types of features as classification characteristics for music styles: timbre and melody features. Because the classification method based on a convolutional neural network ignores the audio’s timing. As a result, we proposed a music classification module based on the one-dimensional convolution of a recurring neuronal network, which we combined with single-dimensional convolution and a two-way, recurrent neural network. To better represent the music style properties, different weights are applied to the output. The GTZAN data set was also subjected to comparison and ablation experiments. The test results outperformed a number of other well-known methods, and the rating performance was competitive.
Weiss responds to a query from a viol student on how to know when to move on from a piece or exercise. As Niccolo Seligmann points out, what relationships we want to have with the pieces we play. ...Students can get stuck on a piece, not playing it well enough to feel like they've mastered it, and yet also unable to make more progress. It can be difficult to work on pieces by yourself and without a goal. Amy Domingues suggests solving that problem by making an objective for yourself. Jacqui Robertson-Wade emphasizes self evaluation and analysis of one's own playing and technique as an important part of developing as a practicer.
Entropy, Style, Voice-leading, Operationalization, Bach INTRODUCTION IN "An Information-Theoretical Method for Comparing Completions of Contrapunctus XIV from Bach's Art of Fugue, " Ivan Paz et al. 3 ...When distributions are compared across musical works, information theory provides quantifiable measurements of difference (here measured as relative entropy) that identify whether something is perceived to be more or less like something else. Figure 1 A, by comparison, shows a shuffled version of the same segment of music, with the exact same pitch and duration distributions (shown in Table 2). In the current study, the main comparison distribution fails to meet these assumptions due, mainly, to the size of the sample: a single work cannot be stochastic, homogeneous, or stationary when representing Bach's style.
The present article brings to attention a theoretical work of the nineteenth century, written in Romanian, concerning the musical scales and structures of the neo-Byzantine music. The writing ...entitled ‘The Scale’ was annexed to ‘The Second Book of Anthology’ (1832), a psaltic manuscript registered at the Romanian Academy Library (BAR) as ms. rom. 2233. The explanations included in the Scale are based on the rules of the hrisantic theory adopted in the Orthodox Church since 1814. These terms include 21 Ottoman makams. The first part of the article deals with general aspects of the researched manuscript, regarding to autorship and content and the second part provides the transliterated version of the text.
Expressive communication in the arts often involves deviations from stylistic norms, which can increase the aesthetic evaluation of an artwork or performance. The detection and appreciation of such ...expressive deviations may be amplified by cultural familiarity and expertise of the observer. One form of expressive communication in music is playing “out of time,” including asynchrony (deviations from synchrony between different instruments) and non-isochrony (deviations from equal spacing between subsequent note onsets or metric units). As previous research has provided somewhat conflicting perspectives on the degree to which deviations from synchrony and isochrony are aesthetically relevant, we aimed to shed new light on this topic by accounting for the effects of listeners' cultural familiarity and expertise. We manipulated (a)synchrony and (non-)isochrony separately in excerpts from three groove-based musical styles (jazz, candombe, and jembe), using timings from real performances. We recruited musician and non-musician participants (N = 176) from three countries (UK, Uruguay, and Mali), selected to vary in their prior experience of hearing and performing these three styles. Participants completed both an aesthetic preference rating task and a perceptual discrimination task for the stimuli. Our results indicate an overall preference toward synchrony in these styles, but culturally contingent, expertise-dependent preferences for deviations from isochrony. This suggests that temporal processing relies on mechanisms that vary in their dependence on low-level and high-level perception, and emphasizes the role of cultural familiarity and expertise in shaping aesthetic preferences.
With a few exceptions, musical taste has been researched via likes or preferences of certain types of music. The present study focuses on disliked music and takes a broad approach to cover ...explanatory strategies related to personal dislikes.
In-depth interviews were conducted with 21 participants in five age groups. Interviewees were asked to prepare a list of their disliked music, and for each item they were asked about the reasons for the dislike. To ensure that the complexity and range of the participants' dislikes and rationales were captured in the analysis, a structuring content analysis as a mostly theory-driven approach was combined with inductive category creation out of the interview data.
The most often mentioned type of dislike was musical style, followed by artist and genre. Five main reference points were identified for describing musical dislikes: the music itself, lyrics, performance, artist, and the people who listen to it. The identified rationales for disliked music were assigned to three larger categories: object-related reasons, such as music-compositional aspects, aesthetic dichotomies or lyrics; subject-related reasons, such as emotional or bodily effects, or discrepancies with the self-image; social reasons, which refer to one's social environment and the taste judgments common to it (in-group) or to other groups of which the participants do not feel part of (out-group). Apart from the rationales for disliked music, the participants described specific reactions when they are confronted with their disliked music, such as emotional, physical, and social reactions.
While musical dislikes have already been shown to fulfill important social functions, the current study extends the rationales to music-related and self-related reasons. Musical dislikes fulfill similar functions to liked music, such as preservation of a good mood, identity expression and construction, strengthening of group cohesion as well as social distinction.
Symbolic music understanding is a critical challenge in artificial intelligence. While traditional symbolic music representations like MIDI capture essential musical elements, they often lack the ...nuanced expression in music scores. Leveraging the advancements in multimodal pre-training, particularly in visual-language pre-training, we propose a groundbreaking approach: the Score Images as a Modality (SIM) model. This model integrates music score images alongside MIDI data for enhanced symbolic music understanding. We also introduce novel pre-training tasks, including masked bar-attribute modeling and score-MIDI matching. These tasks enable the SIM model to capture music structures and align visual and symbolic representations effectively. Additionally, we present a meticulously curated dataset of matched score images and MIDI representations optimized for training the SIM model. Through experimental validation, we demonstrate the efficacy of our approach in advancing symbolic music understanding.
This article examines the creation and early dissemination of John Field's nocturnes, tracing this œuvre through initial publications in St Petersburg by Dalmas (1812; H24–25) to the posthumous ...collected editions by Schuberth and Liszt first released in the 1850s. Inspired by discourse on music and environment, I take the peculiar qualities of Russian night landscapes as a key factor in understanding how these works were composed and then marketed internationally. Although little documentation remains of Field's Russian experiences as described in his own voice, it is possible to reconstruct the place in which he worked through his musical publications, related contemporary descriptions, images and recollections of friends and admirers. These sources shed fresh light on his shift in musical style on relocation from England to Russia. Viewing Field's nocturnes through the lens of this landscape, both real and as imagined by later promoters such as Liszt, offers the opportunity to reach a newly nuanced understanding of Field's array of national identities – Irish, English and Russian – and of his nocturne as a Russia-based idiom.
In recent years, the field of neuroaesthetics has gained considerable attention with music being a favored object of study. The majority of studies concerning music have, however, focused on the ...experience of Western tonal music (TM), which is characterized by tonal hierarchical organization, a high degree of consonance, and a tendency to provide the listener with a tonic as a reference point during the listening experience. We argue that a narrow focus on Western TM may have led to a one-sided view regarding the qualities of the aesthetic experience of music since Western art music from the 20th and 21st century like atonal music (AM) - while lacking a tonal hierarchical structure, and while being highly dissonant and hard to predict - is nevertheless enjoyed by a group of avid listeners. We propose a research focus that investigates, in particular, the experience of AM as a novel and compelling way with which to enhance our understanding of both the aesthetic appreciation of music and the role of predictive models in the context of musical pleasure. We use music theoretical analysis and music information retrieval methods to demonstrate how AM presents the listener with a highly uncertain auditory environment. Specifically, an analysis of a corpus of 100 musical segments is used to illustrate how tonal classical music and AM differ quantitatively in terms of both key and pulse clarity values. We then examine person related, extrinsic and intrinsic factors, that point to potential mechanisms underlying the appreciation and pleasure derived from AM. We argue that personality traits like "openness to experience," the framing of AM as art, and the mere exposure effect are key components of such mechanisms. We further argue that neural correlates of uncertainty estimation could represent a central mechanism for engaging with AM and that such contexts engender a comparatively weak predictive model in the listener. Finally we argue that in such uncertain contexts, correct predictions may be more subjectively rewarding than prediction errors since they signal to the individual that their predictive model is improving.
Tonal harmony is one of the central organization systems of Western music. This article characterizes the statistical foundations of tonal harmony based on the computational analysis of expert ...annotations in a large corpus. Using resampling methods, this study shows that 1) the rank-frequency distribution of chords resembles a power law, i.e. few chords govern a large proportion of the data; 2) chord transitions are referential and chord predictability is significantly affected by distinguished chord features; 3) tonal harmony conveys directedness in time; and 4) tonal harmony operates differently at the hierarchical levels of chords and keys. These results serve to characterize tonal harmony on empirical grounds and advance the methodological state-of-the-art in digital musicology.
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