Search Results (216)

This discussion explores the (dis)engagement of Jamaican RastafarI from the party political process, using RastafarI elder Mortimo Planno’s notion of “politics without a party” as a strand shaping and tying together the multiple threads of the exploration. The discussion examines how RastafarI has engaged with partisan politics/political parties from Independence (1962) until today. It highlights the differing ways of approaching politics among Rastas, including the minority, who have entered representative politics in a bid to [as yet unsuccessfully] change the tribal and compromised state of Jamaican politics. The decentralized nature of the RastafarI movement allows for diverse expressions of RastafarI political thought and action, but can present challenges for unified political mobilization on a large scale. Nonetheless, with or without direct partisan involvement, RastafarI has adapted and re-presented itself in response to changes in the local and global context, thus becoming a potent political force. So, despite this general lack of engagement with “statical” matters, RastafarI is and continues to be a significant political movement on several fronts, through movements, music, and symbols rather than traditional electoral routes. Full article

The impact of cultural identity on music performance anxiety (MPA) is under-researched. This retrospective case study explores the treatment of a professional musician in her 30s who presented with MPA associated with performing music related to her estranged father’s cultural background. The case formulation identified attachment ruptures and negative cognitions associated with her mixed cultural heritage that contributed to an experience of imposterism—referred to in lay literature as ‘racial imposter syndrome’ (RIS). It was hypothesized that RIS served to perpetuate her MPA. An attachment-based approach and Acceptance and Commitment Therapy framework was adopted, drawing on evidence-based treatment for MPA and mixed heritage individuals. The Depression Anxiety Stress Scale-21 (DASS-21), Outcome Rating Scale (ORS) and Session Rating Scale (SRS) were used as outcome measures. These measures fluctuated throughout the therapy. While improvements were observed in depression scores midway through treatment, elevated stress and depression scores at the conclusion of treatment were understood to reflect situational factors related to financial and housing precarity. Nonetheless, at the conclusion of treatment, the client showed improvement in managing MPA, evidenced by her progress in recording an album and reengagement with public performances. This case study adds to the limited research on treating MPA in racially minoritized and mixed-race individuals, Further research is required across larger and more diverse samples to better understand the relationship between MPA and RIS and to develop effective interventions. Full article

Research on children’s singing development is extensive. Different ages, approaches, and variables have been taken into consideration. However, research on singing with text or a neutral syllable is scarce, and findings are inconclusive. This study investigated the influence of singing with text and a neutral syllable on children’s vocal performance. Children aged 4 to 9 (n = 135) participated in two periods of instruction and assessment. In Period One, Song 1 was taught with text and Song 2 with a neutral syllable, and in Period Two, the text was added to Song 2. In each period, children were individually audio-recorded singing both songs. Three independent raters scored the songs’ vocal performances using two researcher-designed rating scales, one for each song, which included the assessment of tonal and rhythm dimensions. Before data analysis, the validity and reliability of the rating scales used to assess vocal performance were examined and assured. The results revealed that 4-, 5-, and 7-year-olds sang Song 1 significantly better in Period One, and 4- and 5-year-olds sang Song 1 significantly better in Period Two. Thus, singing with text seems to favour younger children’s vocal performance. Findings also revealed that girls scored significantly higher than boys for Song 1 in both periods, but not for Song 2 in Period One. The implications of incorporating songs with text and neutral syllables into music programs, as well as the instruments used to assess vocal performances, are discussed. Full article

This study examines the complex process of Islam’s localization in Sudan, focusing on how hospitality, Sufi dhikr, and Mawlid celebrations integrate with Islamic practices. Drawing on three years of qualitative fieldwork, it demonstrates how Sudan’s geography, ethnic diversity, and historical heritage enable the blending of core religious principles with local customs. Sufi brotherhoods—particularly Qādiriyya, Tījāniyya, Shādhiliyya, and Khatmiyya—play a pivotal role in local culture by incorporating traditional musical, choreographic, and narrative art forms into their rituals, resulting in highly dynamic worship and social interaction. In Sudan, hospitality emerges as a near-sovereign social norm, reflecting the Islamic ethics of charity and mutual assistance while remaining deeply intertwined with local traditions. Islam’s adaptability toward local customs is further illustrated by the vibrant drumming, chanting, and dancing that enhance large-scale Mawlid al-Nabi celebrations, uniting Muslims under a religious identity that goes beyond dogmatic definitions. Beyond their spiritual meanings, these Sufi practices and networks also serve as tools for social cohesion, often functioning as support systems in regions with minimal state presence. They help prevent disputes and foster unity, demonstrating the positive impact of a flexible Islam—one that draws on both scripture and local traditions—on peacebuilding in Sudan. While highlighting the country’s social realities, this study offers insights into how Islam can function as a transformative force within society. Full article

Background/Objectives: Cochlear implants (CIs) and hearing aids (HAs) have enhanced auditory rehabilitation in elderly individuals, yet limitations in musical perception and psychosocial integration persist. This systematic review aimed to evaluate the effects of music therapy (MT) on the quality of life (QoL), self-esteem, auditory perception, and cognition in older CI and HA users. Methods: A comprehensive search of PubMed was conducted up to March 2022 following PRISMA guidelines. Studies involving participants aged ≥ 60 years with CIs and/or HAs were included. Ten studies (n = 21,632) met eligibility criteria. Data were extracted and assessed using the Newcastle–Ottawa Scale. Results: MT led to improved sound quality, with HISQUI19 scores rising from 60.0 ± 21.8 to 74.2 ± 27.5. Early MT exposure was associated with significantly better MUMU outcomes (p = 0.02). Bilateral CI users showed enhanced stereo detection (52% to 86%), and CI + HA users achieved CNC scores exceeding 95%. Postlingual CI users outperformed prelingual peers in musical discrimination (9.81 vs. 3.48; p < 0.001). Long-term HA use was linked to better a QoL and reduced loneliness. Conclusions: While music therapy appears to support auditory and psychosocial functioning in hearing-impaired older adults, the absence of randomized controlled trials limits causal inference regarding its effects. These results support its integration into hearing rehabilitation strategies for older adults. Full article

In the field of music notation recognition, while the recognition technology for common notation systems such as staff notation has become quite mature, the recognition techniques for traditional Chinese notation systems like guqin tablature (jianzipu) and Kunqu opera gongchepu remain relatively underdeveloped. As an important carrier of China’s thousand-year musical culture, the digital preservation and inheritance of Kunqu opera’s Gongche notation hold significant cultural value and practical significance. By addressing the unique characteristics of Gongche notation, this study overcomes the limitations of Western staff notation recognition technologies. By constructing a deep learning model adapted to the morphology of Chinese character-style notation symbols, it provides technical support for establishing an intelligent processing system for Chinese musical documents, thereby promoting the innovative development and inheritance of traditional music in the era of artificial intelligence. This paper has constructed the LGRC2024 (Gong-che notation based on Lilu Qu Pu) dataset. It has also employed data augmentation operations such as image translation, rotation, and noise processing to enhance the diversity of the dataset. For the recognition of Gong-che notation, the YOLOv8 model was adopted, and the network performances of its lightweight (n) and medium-weight (m) versions were compared and analyzed. The superior-performing YOLOv8m was selected as the basic model. To further improve the model’s performance, SimAM, Triplet Attention, and Multi-scale Convolutional Attention Module (MSCAM) were introduced to optimize the model. The experimental results show that the accuracy of the basic YOLOv8m model increased from 65.9% to 78.2%. The improved models based on YOLOv8m achieved recognition accuracies of 80.4%, 81.8%, and 83.6%, respectively. Among them, the improved model with the MSCAM module demonstrated the best performance in all aspects. Full article

Objective: This study aims to investigate the feasibility of an online music therapy protocol for individuals previously diagnosed with COVID-19, focusing on their perceptions of their respiratory symptoms and the intervention’s impact on psychosocial measures. Methods: A within-subject experimental design was applied to examine an eight-week weekly online music therapy protocol, including singing, wind instrument playing, and music visualizations. All self-report data were collected bi-weekly throughout the 16-weeks study period, including baseline and post-tests. The measures for respiratory symptoms included the Medical Research Council’s Dyspnea Scale (MRC Dyspnea), Chronic Respiratory Questionnaire-Mastery Scores (CRQ Mastery), and Visual Analogue Scale for breathlessness. The measures for the secondary psychosocial outcomes were the Beck Depression Inventory-Short Form, the Generalized Anxiety Disorder 7-item, the Hospital Anxiety and Depression Scale, the Fatigue Severity Scale, the Epworth Sleepiness Scale, the EuroQol 5-Dimension 5-Level, and the Connor-Davidson Resilience Scale. Results: Twenty-four participants were enrolled. The participants perceived a reduction in respiratory symptoms, and shortness of breath (MRC Dyspnea). Planned comparisons showed significant decreases in MRC from baseline to post-treatment (p = 0.008). The mixed-effects model, including pre-baseline and post-treatment, was significant (p < 0.001). Significant changes in Breathing VAS were consistent with improvements in MRC Dyspnea, showing a significant baseline-to-post difference (p = 0.01). The CRQ Mastery showed significant improvements from baseline to Week 12 (p < 0.001). No significant changes were observed in other secondary measures. Conclusions: Our preliminary findings suggest that this protocol is feasible, and as a result, may help individuals previously diagnosed with COVID-19 to cope with lasting respiratory symptoms and improve their perception of shortness of breath. Live music-making, including playing accessible wind instruments and singing, may contribute to an increase sense of control over breathing. As this was a feasibility study, we conducted multiple uncorrected statistical comparisons to explore potential effects. While this approach may increase the risk of Type I error, the findings are intended to inform hypotheses for future confirmatory studies rather than to draw definitive conclusions. Full article

The development of a Spanish musical profile questionnaire, designed to assess both objective aspects of musical engagement and psychological dimensions, represents a significant advancement in the fields of music psychology and music education. Grounded in prior research and created by experts in music education, this instrument offers a comprehensive portrait of musicians by capturing their training, experience, and psychological characteristics. A total of 261 musicians, ranging in age from 16 to 61 years, were recruited through incidental sampling to complete the questionnaire. The final version encompasses both objective indicators of musical dedication and a psychological profile scale. The psychometric evaluation of the scale supported a robust three-factor model comprising “Musical Self-Perception”, “Personal Cost of Music”, and “Existential Contribution of Music”. The 10-item scale demonstrated acceptable internal consistency, along with strong criterion and convergent validity, affirming the instrument’s reliability. The discussion regarding the inclusion or exclusion of items related to theoretical content reflects an evidence-based approach aimed at continuous refinement of the tool. Furthermore, the identification of future directions, including exploration of additional psychological dimensions and potential adaptations for diverse cultural or educational contexts, underscores a forward-looking commitment to the ongoing development and applicability of the questionnaire. Full article

This study explores the novel integration of data sonification into hydraulic engineering by translating transient pressure fluctuations in a hydraulic system into sound. Using a simple hydraulic model built in KYPipe, a pump connected to a reservoir and a tank was simulated to trip, causing transient pressure changes. These pressure variations were mapped onto the C-major scale using Microsoft Excel, creating an auditory representation. The methodology included generating a sound library using recorded piano samples and applying VBA code to link pressure values with musical notes. The results demonstrated that sonification provides an innovative means of presenting transient hydraulic phenomena, enabling users to identify critical events such as pressure spikes audibly. While the study highlights challenges, such as computational limitations and resolution trade-offs in mapping, it opens pathways for employing auditory data representation in engineering contexts. Future work could focus on expanding audio sample libraries and optimizing computational methods to improve resolution and usability. Full article

Instrument recognition is a crucial aspect of music information retrieval, and in recent years, machine learning-based methods have become the primary approach to addressing this challenge. However, existing models often struggle to accurately identify multiple instruments within music tracks that vary in length and quality. One key issue is that the instruments of interest may not appear in every clip of the audio sample, and when they do, they are often unevenly distributed across different sections of the track. Additionally, in polyphonic music, multiple instruments are often played simultaneously, leading to signal overlap. Using the same overlapping audio signals as partial classification features for different instruments will reduce the distinguishability of features between instruments, thereby affecting the performance of instrument recognition. These complexities present significant challenges for current instrument recognition models. Therefore, this paper proposes a multi-instance multi-scale graph attention neural network (MMGAT) with label semantic embeddings for instrument recognition. MMGAT designs an instance correlation graph to model the presence and quantitative timbre similarity of instruments at different positions from the perspective of multi-instance learning. Then, to enhance the distinguishability of signals after the overlap of different instruments and improve classification accuracy, MMGAT learns semantic information from the labels of different instruments as embeddings and incorporates them into the overlapping audio signal features, thereby enhancing the differentiability of audio features for various instruments. MMGAT then designs an instance-based multi-instance multi-scale graph attention neural network to recognize different instruments based on the instance correlation graphs and label semantic embeddings. The effectiveness of MMGAT is validated through experiments and compared to commonly used instrument recognition models. The experimental results demonstrate that MMGAT outperforms existing approaches in instrument recognition tasks. Full article

Deciphering the structural hierarchy of musical compositions is indispensable for a range of music analysis applications, encompassing feature extraction, data compression, interpretation, and visualization. In this paper, we introduce a quantitative model grounded in fractal theory to evaluate the significance of individual notes within a musical piece. To analyze the quantized note importance, we adopt a rhythm-based approach and propose a series of detection operators informed by fundamental rhythmic combinations. Employing the Mamba model, we carry out recursive detection operations that offer a hierarchic understanding of musical structures. By organizing the composition into a tree data structure, we achieve an ordered layer traversal that highlights the music piece’s multi-dimensional features. Musical compositions often exhibit intrinsic symmetry in their temporal organization, manifested through repetition, variation, and self-similar patterns across scales. Among these symmetry properties, fractality stands out as a prominent characteristic, reflecting recursive structures both rhythmically and melodically. Our model effectively captures this property, providing insights into the fractal-like regularities within music. It also proves effective in musical phrase boundary detection tasks, enhancing the clarity and visualization of musical information. The findings illustrate the model’s potential to advance the quantitative analysis of music hierarchy, promoting novel methodologies in musicological research. Full article

Theaters in ancient Pompeii played a vital role in Roman entertainment, shaping the auditory experiences of spectators. This study examines the acoustic properties of the Amphitheater, the Grand Theater, and the Odeon using impulse response (IR) analysis to reconstruct their soundscapes. Next, the study considers the impact of typical musical instruments, vocal performances, and ambient sounds—such as gladiatorial combat—on these spaces’ acoustics. Findings reveal significant differences in reverberation times, sound clarity, and spatial characteristics, shaped by each theater’s design. These sites, preserved after the eruption of Mount Vesuvius, provide a unique opportunity to analyze how architecture influenced sound propagation. The Amphitheater, with its vast open structure, enhanced large-scale events, while the Grand Theater’s semi-enclosed design balanced musical and theatrical performances. The Odeon, the most intimate of the three, prioritized speech clarity. These insights highlight how Roman architects engineered performance spaces to accommodate diverse entertainment forms. By combining acoustic measurements with historical context, this research offers a deeper understanding of ancient Pompeii’s soundscapes and the auditory experiences of its inhabitants and offers insights for composition and soundscape creations that take inspiration from these prominent historical architectural and cultural icons whilst exploring its potential within contemporary immersive listening practices. Full article

This paper integrates concepts from neurobiology, marketing and musicology to propose a causal model of music appreciation and exploratory listening, using directed acyclic graphs (DAGs) and structural equation models (SEMs). The key concepts are music appreciation (measured on a scale from 1 to 10), evaluations, experiences and the qualities of musical features, which the listeners explore and describe from a first-person perspective. The qualities are understood in terms of a satisfaction or dissatisfaction rating of operational features. The development of the causal model is based on a reiterative methodology involving surveys. Applying the causal model to a large survey of 800 listeners reveals that listeners adopt a slightly different causal pathway for their appreciation of liked versus disliked music. When listeners dislike music, the source of their dissatisfaction is more consistently attributed to the perceived or missed musical qualities rather than to their personal experiences. The iterative methodology and causal modeling offer a foundation for further investigation and refinement in various listening contexts. Full article

Understanding tonal structures in Renaissance music has been a long-standing musicological problem. Computational analysis on a large scale could shed new light on this. Encoded scores provide easy access to pitch content, but the availability of such data is low. This paper addresses this shortage of data by exploring the potential of audio recordings. Analysing audio, however, is challenging due to the presence of harmonics, reverb and noise, which may obscure the pitch content. We test several multiple pitch estimation models on audio recordings, using encoded scores from the Josquin Research Project (JRP) as a benchmark for evaluation. We present a dataset of multiple pitch estimations from 611 compositions in the JRP. We use the pitch estimations to create pitch profiles and pitch class profiles, and to estimate the lowest final pitch of each recording. Our findings indicate that the Multif0 model yields pitch profiles, pitch class profiles and finals most closely aligned with symbolic encodings. Furthermore, we found no effect of year of recording, number of voices and ensemble composition on the accuracy of pitch estimations. Finally, we demonstrate how these models can be applied to gain insight into tonal structures in early polyphony. Full article

This research contributes to the studies on the origins and transformations of Tchaikovsky’s Children’s Album, Op. 39 using the linguistic methods of discourse, metaphor, and comparative analysis to explore a number of connected questions and their impact on how the audiences and scholars perceive and understand the compositions. These methods are supported by the technology provided by computational linguistics, such as large language models along with music analysis algorithms based on signature pattern elicitation. This article examines how artificial intelligence technologies can shed light on the differing views on the Children’s Album. The meanings and implications of the published reordering of the pieces are explored. The influence of Schumann’s Album for the Young and the broader pedagogical and cultural significance of editorial transformations is investigated. Through this interdisciplinary approach, this study offers new insights into the compositional intent and interpretive possibilities of Tchaikovsky’s work. The presented results of the musicology, literary, computational, and linguistic analyses complement the few scholarly studies aimed at unveiling the intriguing metaphors and connections of the Children’s Album, which tend to remain in the shadows of his larger-scale piano and symphonic works. Full article