Hasil untuk "Literature on music"

J. Váradi

Social-emotional learning (SEL) is a topic of increasing focus in the education sector. SEL is the process by which children acquire the knowledge, skills, and attitudes to effectively recognize and manage emotions, to formulate positive goals, to feel empathy for others, to establish and maintain functioning social relationships. It develops to take responsible decisions, determine students’ successful academic performance, transformation into adulthood, useful work, a good quality of life, and well-being. By the end of the 20th century the educational role of music has come into the spotlight, and in addition to the impact of music on the development of general skills, its social and emotional effects are also the subject of research. This paper undertakes to explore the literature about the connections between music education and social-emotional skill development. For the collection and analysis of information, online sources of peer-reviewed scientific journals in addition to the university library were used. The study also examined the relationship between social-emotional learning and the world-wide well-known Kodály Concept and the effect of Kodály’s vision of music education as a forerunner of socio-emotional skills development. The relationship between social-emotional skills and music was explored by reviewing the international music-specific literature from music psychology, music education, music therapy, and music for health and wellbeing. In order to illuminate the problem and to develop a holistic approach, the 100 studies presented here summarize research findings made and presented in different countries around the world.

Shumeng Zhang, Raul Masu, Mela Bettega et al.

This paper presents a systematic literature review of music technology tailored for blind and low vision (BLV) individuals. Music activities can be particularly beneficial for BLV people. However, a systematic approach to organizing knowledge on designing accessible technology for BLV people has yet to be attempted. We categorize the existing studies based on the type of technology and the extent of BLV people’s involvement in the research. We identify six main categories of BLV people-oriented music technology and highlight four key trends in design goals. Based on these categories, we propose four general insights focusing on (1) spatial awareness, (2) access to information, (3) (non-verbal) communication, and (4) memory. The identified trends suggest that more empirical studies involving BLV people in real-world scenarios are needed to ensure that technological advancements can enhance musical experiences and social inclusion. This research proposes collaborative music technology and inclusive real-world testing with the target group as two key areas missing in current research. They serve as a foundational step in shifting the focus from “accessible technology” to “inclusive technology” for BLV individuals within the broader field of accessibility research.

Wafa A. Nawwab, Sultan A. Alqasim, Nada N. Alghamdi et al.

Sickle cell disease (SCD) is a genetic disorder characterized by rigid, sickle-shaped red blood cells, leading to complications such as vaso-occlusive crises (VOCs). These acute pain episodes are the most common reason for emergency visits and hospitalizations in adults with SCD. his narrative review evaluated the efficacy of pharmacological and non-pharmacological treatments for acute pain crises in adults with SCD, with secondary attention to safety outcomes, including side effects, treatment duration, hospital stay, and readmission rates. Materials and Methods: A literature search was conducted in PubMed, Cochrane Library, and Google Scholar up to August 20, 2024, focusing on randomized controlled trials (RCTs) in English involving adult patients. Relevant studies were reviewed, and findings were synthesized narratively. The result Twelve RCTs involving 576 adults were included. Most studies were of good quality, though two had high risk and two had unclear risk of bias. Interventions included L-glutamine, pregabalin, regadenoson, ketorolac, individualized opioid protocols, progressive muscle relaxation, and music therapy. L-glutamine and individualized opioid protocols consistently reduced pain intensity. Pregabalin and ketorolac showed mixed results, while non-pharmacological interventions provided modest pain relief or improved mood. Overall, individualized treatment approaches appeared more effective than uniform protocols, though variability in study design and outcomes limits generalizability. IIn conclusion Twelve RCTs involving 576 adults were included. Most studies were of good quality, though two had high risk and two had unclear risk of bias. Interventions included L-glutamine, pregabalin, regadenoson, ketorolac, individualized opioid protocols, progressive muscle relaxation, and music therapy. L-glutamine and individualized opioid protocols consistently reduced pain intensity. Pregabalin and ketorolac showed mixed results, while non-pharmacological interventions provided modest pain relief or improved mood. Overall, individualized treatment approaches appeared more effective than uniform protocols, though variability in study design and outcomes limits generalizability. TEK therapy and L-glutamine were most effective for pain reduction, while pregabalin and regadenoson were safe and promising. Non-pharmacological interventions may support standard care, but further high-quality RCTs are recommended to confirm efficacy and safety.

Setareh Beheshti, Iman Fakhr, saeed Majidi

Form is one of the most important and challenging concepts in music. Music scholars have long offered diverse interpretations and definitions of musical form, but the multiplicity of interpretations can sometimes lead to confusion and impede the attainment of a clear understanding of the structure of musical works. This is partly due to ‘reverse-engineering.’ When a compositional form is created, the composer may or may not be thinking primarily about structure.  The aesthetic message is at the forefront of the composer’s creative conscience followed by thematic phrases, the connective bridges, timbres of sound (orchestration) and most importantly artistic satisfaction.  Theoreticians get involved with a piece of music after it has been written, hence their point of view is an approximation of the composer’s intent.  Over the years, formal structure has become conclusive evidence for formal musical analysis, even though it is in the aftermath of the creative process.  This is the main reason why theories and examples are often hindered by exceptions and compromised by unique forms and structures. Over the years certain various analytical models have been widely accepted in order to highlight or emphasize certain structural elements in musical forms. The most common model is the sonata form which for the most part reflects the structural form of most repertoire from the mid-18th century up to the present.  But this model like others, only illuminates specific aspects of a musical structure, while overlooking compositional details that can stand to be further investigated. Therefore, conducting multifarious analyses on one musical structure can reveal more facets and result in a deeper understanding of the work. However, one must be aware that diversity in analytical perspectives can also lead to multiplicity and ambiguity in understanding musical structure, especially in the Romantic period. For this reason, Agawu, based on the archetypal tripartite structure of beginning, middle, and end, has proposed a theory for analyzing the structure of Romantic music. By simplifying the overall viewpoint of a musical form, Agawu allows for multiple persperctives or analysis to co-exist within one oeuvre.This qualitative research endeavors to apply Agawu's theory to provide a unified formulation of two different analytical approaches to the structure of Mendelssohn's Violin Concerto; a work whose structural innovations have been little studied. In this regard, using a descriptive-analytical method, the structure of the case study was analyzed using both the sonata form and arch form approaches, and it was determined which aspects of the structure were clarified by these approaches. Then, using Agawu's theory based on the two criteria of position and function, the structure of the case study was analyzed, and finally, two other analytical approaches were also formulated under Agawu's tripartite model to achieve a unified understanding of the different analytical models. By using a more general and simplified model, as suggested by Agawu, musicians and theoreticians are not limited to looking at a musical work with just one analysis.  By allowing mulitiple perspectives for interpretation and examination, a deeper understanding of the creative process can be achieved.

Bradley Hauer, Colin Choi, Abram Hindle et al.

The Dorabella cipher is an encrypted note written by English composer Edward Elgar, which has defied decipherment attempts for more than a century. While most proposed solutions are English texts, we investigate the hypothesis that Dorabella represents enciphered music. We weigh the evidence for and against the hypothesis, devise a simplified music notation, and attempt to reconstruct a melody from the cipher. Our tools are n-gram models of music which we validate on existing music corpora enciphered using monoalphabetic substitution. By applying our methods to Dorabella, we produce a decipherment with musical qualities, which is then transformed via artful composition into a listenable melody. Far from arguing that the end result represents the only true solution, we instead frame the process of decipherment as part of the composition process.

Harin Lee, Elif Çelen, Peter Harrison et al.

Human annotations of mood in music are essential for music generation and recommender systems. However, existing datasets predominantly focus on Western songs with terms derived from English, which may limit generalizability across diverse linguistic and cultural backgrounds. We introduce 'GlobalMood', a novel cross-cultural benchmark dataset comprising 1,180 songs sampled from 59 countries, with large-scale annotations collected from 2,519 individuals across five culturally and linguistically distinct locations: U.S., France, Mexico, S. Korea, and Egypt. Rather than imposing predefined emotion and mood categories, we implement a bottom-up, participant-driven approach to organically elicit culturally specific music-related emotion terms. We then recruit another pool of human participants to collect 988,925 ratings for these culture-specific descriptors. Our analysis confirms the presence of a valence-arousal structure shared across cultures, yet also reveals significant divergences in how certain emotion terms (despite being dictionary equivalents) are perceived cross-culturally. State-of-the-art multimodal models benefit substantially from fine-tuning on our cross-culturally balanced dataset, particularly in non-English contexts. Broadly, our findings inform the ongoing debate on the universality versus cultural specificity of emotional descriptors, and our methodology can contribute to other multimodal and cross-lingual research.

Venkatakrishnan Vaidyanathapuram Krishnan, Noel Alben, Anish Nair et al.

Music source separation demixes a piece of music into its individual sound sources (vocals, percussion, melodic instruments, etc.), a task with no simple mathematical solution. It requires deep learning methods involving training on large datasets of isolated music stems. The most commonly available datasets are made from commercial Western music, limiting the models' applications to non-Western genres like Carnatic music. Carnatic music is a live tradition, with the available multi-track recordings containing overlapping sounds and bleeds between the sources. This poses a challenge to commercially available source separation models like Spleeter and Hybrid Demucs. In this work, we introduce 'Sanidha', the first open-source novel dataset for Carnatic music, offering studio-quality, multi-track recordings with minimal to no overlap or bleed. Along with the audio files, we provide high-definition videos of the artists' performances. Additionally, we fine-tuned Spleeter, one of the most commonly used source separation models, on our dataset and observed improved SDR performance compared to fine-tuning on a pre-existing Carnatic multi-track dataset. The outputs of the fine-tuned model with 'Sanidha' are evaluated through a listening study.

Yifang Zhang, Beh Wen Fen, Chao Zhang et al.

The advent of artificial intelligence (AI) has brought significant and transformative alterations to traditional music education. This study examines the progress of AI technology in music education by conducting a systematic review using the PRISMA methodology. Articles were selected for inclusion based on the criterion of specifically describing the utilization of AI in the instruction and acquisition of music. The search was performed on April 9, 2024, via the Web of Science and SCOPUS databases. The search terms “music education” and “artificial intelligence” were employed to ascertain relevant scholarly research. The group of papers underwent scrutiny by various researchers to ascertain their adherence to the established criteria. The articles that were verified by a minimum of two researchers were chosen. 31 articles were finally screened, and the results were divided into two sections: the development of AI in music education and innovative music pedagogy based on AI. A key finding is that the implementation of bibliometric analyses suggests that AI research in music education is still in its infancy. Prior research has primarily concentrated on music instruction at the university level, with a particular emphasis on the integration of AI in music education in China. In addition, this study identifies four specific facets of AI through the reshaping of music pedagogy: enhancing personalized music teaching, providing timely feedback on learning, supporting interactive experiences, and providing organized digital materials.

Jieun Park, Youjin Choi, KyungMyun Lee

Poorna Fernando, Thilini V. Mahanama, M. Wickramasinghe

In the world of musical creation, the integration of artificial intelligence (AI) represents a significant paradigm shift in emotional engagement. This research investigates the human emotional responses evoked when listening to AI-composed music. Focused on figuring out the emotional impact of AI-composed music, the study explores the complex relationship between human emotional experiences and compositions crafted by AI algorithms. Through a comprehensive literature review, this paper examines existing methodologies, insights, and gaps in understanding the emotional dimensions of AI-composed music. Major findings reveal that while AI software like artificial intelligence virtual artist (AIVA) shows it can help explore emotional authenticity, ongoing doubt and preference for music made by humans highlight the need for more research. Attitudes of both listeners and music professionals toward AI-composed music are characterized by skepticism and negative perceptions, emphasizing the urgency to address reservations and investigate the unique emotional qualities of AI-composed music. Furthermore, the complex nature of music emotion recognition, influenced by factors such as music genre, cultural perspective, and age group, complicates understanding emotional responses to both human-created and AI-composed music. The paper supports the development of analytical methods, particularly through machine learning and deep learning approaches, to enhance understanding of the complexities of emotional responses and improve AI music composition. A human-experience-centered framework is proposed to address subjectivity in assessing emotional responses to music. This research aims to understand the details of emotional responses and find out if AI-composed music can really evoke emotions comparable to human-created compositions.

Shreya Meda, Joyce Gyamfi, Kahini Patel et al.

BackgroundHypertension (HTN) currently affects over 120 million Americans, in the United States (US). Thus, the implementation of evidence-based interventions (EBI) for blood pressure (BP) reduction is pivotal in minimizing this burden. We sought to evaluate evidence from published literature on the effectiveness of musical interventions for BP reduction within the US.MethodsA systematic review of studies that utilize music interventions to manage BP was conducted in October of 2022. An extensive search of several databases utilizing MeSH terms and relevant keywords was conducted for articles published through October 2022. An updated search was conducted in October 2023 to identify additional studies.Results2,381 studies were screened for title/abstract relevancy. 1,885 studies were deemed irrelevant, and 495 studies were examined for full-text review; of which 384 were excluded due to being non-US-based. Overall, 25 studies were found where BP was the primary outcome and discussed musical interventions within the US. Of the 25 studies, 72% reported a significant decrease in BP after the administration of a musical intervention and only 28% reported the race and ethnicity of participants.ConclusionThere are limited studies that examine the effect of music interventions on BP reduction in the US, as a primary outcome. However, based on the evidence, musical interventions are effective for BP reduction. Moreover, the studies that were conducted in the US include a low percentage of high-risk racial and ethnic minority populations. Future EBI should target this underserved/high-burden group to improve disparity gaps within BP reduction via non-pharmacological means. Systematic Review RegistrationOpen Science Framework, doi: 10.17605/OSF.IO/4G3EB.

Maciej Jochymczyk

Władysławowi Leszczyńskiemu (1616–80), kapelmistrzowi zespołu jasnogórskiego, przypisywano dotychczas dwie zachowane w Archiwum Krakowskiej Kapituły Katedralnej msze: Missa per octavas i Missa cum Credo per octavas. Jak wykazano w niniejszym artykule, drugi z utworów w rzeczywistości nie jest jego dziełem, a zmienioną wersją Missae pro Nativitate Domini Nostri Jesu Christi zachowanej również w zbiorach wawelskich, sygnowanej inicjałami „M.M.” i przypisywanej Marcinowi Mielczewskiemu. Wskazano ponadto kolejny, nieznany wcześniej przekaz tej mszy i poddano refleksji kwestię jej atrybucji.

Daniel Mota-Rojas, Alexandra L. Whittaker, Adriana Domínguez-Oliva et al.

Several types of enrichment can be used to improve animal welfare. This review summarizes the literature on the use of mechanical brushes, tactile udder stimulation, music, and visual stimuli as enrichment methods for dairy cows. Mechanical brushes and tactile stimulation of the udder have been shown to have a positive effect on milk yield and overall behavioral repertoire, enhancing natural behavior. Classical music reduces stress levels and has similarly been associated with increased milk yield. A slow or moderate tempo (70 to 100 bpm) at frequencies below 70 dB is recommended to have this positive effect. Evidence on the impacts of other types of enrichment, such as visual stimulation through mirrors, pictures, and color lights, or the use of olfactory stimuli, is equivocal and requires further study.

Maria S. Frolova

In 2021-2023 In Yekaterinburg, 3 volumes of author's essays were published on the development of the cultural sphere of the capital of the Urals. The release of review texts was initiated by the Department of Culture of the Yekaterinburg Administration. On 864 pages, using archival materials, unique historical and contemporary photographs, the “spirit of the development of the arts” is presented - music, theater and cinema in Volume 1, sculpture, painting and architecture in Volume 2, literature, art education and the educational system in Volume 3. The chosen genre - essays - is original and productive. Texts are a form of summing up, recording successes in the development of the Yekaterinburg/Sverdlovsk sphere of culture. The tercentenary anniversary of Yekaterinburg (the city can be scientifically categorized as a regional or peripheral capital), which took place in 2023, is an occasion for reflection and further planning. Richly illustrated, gift-type books are deep and original from the point of view of analytics of the development of the cultural sphere. The authors were leading academic researchers and employees of the largest cultural institutions of Yekaterinburg - the Sverdlovsk Regional Museum of Local Lore, UrFU named after the first President of Russia B. N. Yeltsin, the Museum of the History of Yekaterinburg, the Sverdlovsk Music School named after P. I. Tchaikovsky. Using the general scientific critical method, methods of synthesis and analysis, the text of the review provides a brief overview of all three volumes of essays, characterizes the merits of the publication, and provides criticism.

Javier Olvera-Fernández, Ramón Montes-Rodríguez, Almudena Ocaña-Fernández

Yang Yang, G. Welch

Based on findings from a large meta-data-based literature survey, this article is intended to provide a comprehensive synthesis of key features of China’s music education system as seen through the lens of n = 116 major research studies, drawn from a total of N = 3,257 high-impact Chinese journal articles published during 2007 to 2019. The synthesis suggests that (1) education reform, aesthetic education, Chinese traditional music and cultural identity were found to be the most prominent topics across all levels of formal music education; and (2) in most studies, government financial support, policy priorities, curriculum enforcement and paedagogical innovation are proposed as general cures to address perceptions of an unsatisfactory situation within music education. However, (3) by relating these findings to national statistics, a clear gap is identified between several research studies and actual social contexts, suggesting a possible deviation of academic communities from realistic educational and social challenges. Thus, external validity issues related to these studies are also discussed critically, along with their potential influence on views of what counts as Chinese music education in domestic and international research communities.

Elia Pizzolitto

Music is the background of life, representing an international language that connects different cultures. It is also significant with respect to economies, markets, and businesses. The literature in the music field has identified several issues related to the role of digitalization in the revolution of music, the distribution of music products, the management and organization of music events, music marketing strategies, and the position of musicians as entrepreneurs. This paper comprises a systematic literature review of the most recent articles discussing the numerous connections between music, business, and management (2017–2022). Through a rigorous protocol, this research discusses the effects of the digital revolution on the music industry, with particular reference to the persisting oligopoly of major labels and the new business models that integrate music streaming and social networks. The findings show the renaissance and relevance of live music events, the fundamental role of segmentation strategies for managing festivals, and the limited presence of sustainability as a priority during festivals and events management. Furthermore, the literature highlights the relevance of discussions concerning musicians’ identity, especially in light of the complex relationship between the bohemian and the entrepreneurial nature of their profession. This is followed by numerous reflections on future research opportunities, recommending theoretical and empirical in-depth studies of music industry competition, futuristic management philosophies and business models, and the roles of technology, sustainability, and financial elements in fostering artists’ success in the digital era. Finally, the paper discusses business models and strategies for musicians, festivals management, stores, and sustainability.

Betty Bauman-Field

Students who have experienced trauma may be especially likely to present challenging behaviors in the classroom. With an increase of trauma-affected students in music classrooms, it is important for music educators to consider classroom management (CM) practices that support trauma-affected students’ healing without triggering students’ trauma responses. In this review of literature, I discuss childhood trauma and trauma-informed positive education (TIPE), research-supported CM strategies in music education, and the ways in which these CM practices do or do not support the trauma-informed approach outlined by TIPE. In addition, I provide my own definition for trauma-informed CM in music education and suggest implications for the music education field.

W. Liu

Daniel Kevin Kurniawan, Gregorius Revyanno Alexander, Sidharta Sidharta

Recently, Artificial Intelligence development and implementation are becoming faster and more popular. Artificial Intelligence has appeared to help humans in their daily activities. Several examples that are currently hype are Chat-GPT, and AI Art. With the emergence of applications like Chat-GPT many people have started using applications that have Artificial Intelligence in it. However, there are still rare applications or research that discuss the implementation of Artificial Intelligence or deep learning in music. Therefore, this research will conduct a systematic literature review (SLR) on Deep Learning in music. In this systematic literature review we will research and answer three research questions. Those research question are, What kind of deep learning architecture that most widely used for developing, classifying, and making music; What implementations of deep learning can be done in music, Whether the existence of Artificial Intelligence / Deep learning can help musicians or composers in making music. Predetermined research questions will be answered using the Kitchenham & Cochrane method. From the results of the analysis that has been carried out we concluded that the deep learning methods that are widely used for training deep learning in music are CNN and RCNN, While the implementation of deep learning in music is used for classification and recommendation systems. For conclusion in this paper, we conclude that deep learning can be used to help musicians and composers in creating music.