Hasil untuk "Literature on music"

Marion Baranes, Romain Hennequin, Elena V. Epure

Although annotated music descriptor datasets for user queries are increasingly common, few consider the user's intent behind these descriptors, which is essential for effectively meeting their needs. We introduce MusicRecoIntent, a manually annotated corpus of 2,291 Reddit music requests, labeling musical descriptors across seven categories with positive, negative, or referential preference-bearing roles. We then investigate how reliably large language models (LLMs) can extract these music descriptors, finding that they do capture explicit descriptors but struggle with context-dependent ones. This work can further serve as a benchmark for fine-grained modeling of user intent and for gaining insights into improving LLM-based music understanding systems.

Darius Afchar, Gabriel Meseguer-Brocal, Romain Hennequin

In the face of a new era of generative models, the detection of artificially generated content has become a matter of utmost importance. In particular, the ability to create credible minute-long synthetic music in a few seconds on user-friendly platforms poses a real threat of fraud on streaming services and unfair competition to human artists. This paper demonstrates the possibility (and surprising ease) of training classifiers on datasets comprising real audio and artificial reconstructions, achieving a convincing accuracy of 99.8%. To our knowledge, this marks the first publication of a AI-music detector, a tool that will help in the regulation of synthetic media. Nevertheless, informed by decades of literature on forgery detection in other fields, we stress that getting a good test score is not the end of the story. We expose and discuss several facets that could be problematic with such a deployed detector: robustness to audio manipulation, generalisation to unseen models. This second part acts as a position for future research steps in the field and a caveat to a flourishing market of artificial content checkers.

Oluseun Sunday Odusanya, Zacchaeus Adelere Adesokan, Damaris T’Oluwalope Aremu et al.

The paper addresses women's participation in church choral ministries, focusing on women as conductors. Despite the growing recognition of women leaders, women's involvement in music ministries is often challenged by gender- and tradition-based barriers. The study examines how women overcome these barriers, shape worship styles, and enrich the church's spiritual and musical life. This study employs a qualitative research method, utilising in-depth interviews with 15 women choral conductors, surveys of 30 church music directors across various denominations, and a critical analysis of historical and contemporary literature. Thematic analysis was used to interpret qualitative data, identifying key themes related to gender dynamics, leadership experiences, and musical influence within church settings. The research is guided by feminist theory, as outlined by Hooks (2000), and ecclesiological theory proposed by Johnson (2015). The paper outlines how women have shaped worship experiences and congregations' spiritual and artistic identity through historical examples, personal narratives, and contemporary practice. By juxtaposing their leadership within the discourses of religion and art, this article pays tribute to women conductors who employ their batons to glorify God and inspire others in the sacred domain of church ministries. The paper concludes that to tap the full potential of women in church music, there needs to be a deconstruction of the gendered barriers that continue to constrain their leadership opportunities. Churches must proactively offer mentorship, professional training, and equal leadership roles for women. Future research should explore the impact of cultural and denominational variations on women's leadership equality in church music, investigate the long-term career trajectories of women conductors, and examine the role of theological education in shaping gender-inclusive music ministries.

Jinju Kim, Taehan Kim, Abdul Waheed et al.

AI music generation is rapidly emerging in the creative industries, enabling intuitive music generation from textual descriptions. However, these systems pose risks in exploitation of copyrighted creations, raising ethical and legal concerns. In this paper, we present preliminary results on the first application of machine unlearning techniques from an ongoing research to prevent inadvertent usage of creative content. Particularly, we explore existing methods in machine unlearning to a pre-trained Text-to-Music (TTM) baseline and analyze their efficacy in unlearning pre-trained datasets without harming model performance. Through our experiments, we provide insights into the challenges of applying unlearning in music generation, offering a foundational analysis for future works on the application of unlearning for music generative models.

Liam Pram, Fabio Morreale

AI systems for music generation are increasingly common and easy to use, granting people without any musical background the ability to create music. Because of this, generative-AI has been marketed and celebrated as a means of democratizing music making. However, inclusivity often functions as marketable rhetoric rather than a genuine guiding principle in these industry settings. In this paper, we look at four generative-AI music making systems available to the public as of mid-2025 (AIVA, Stable Audio, Suno, and Udio) and track how they are rhetoricized by their developers, and received by users. Our aim is to investigate ideologies that are driving the early-stage development and adoption of generative-AI in music making, with a particular focus on democratization. A combination of autoethnography and digital ethnography is used to examine patterns and incongruities in rhetoric when positioned against product functionality. The results are then collated to develop a nuanced, contextual discussion. The shared ideology we map between producers and consumers is individualist, globalist, techno-liberal, and ethically evasive. It is a 'total ideology' which obfuscates individual responsibility, and through which the nature of music and musical practice is transfigured to suit generative outcomes.

Suhwan Choi, Kyu Won Kim, Myungjoo Kang

We introduce Multimodal Matching based on Valence and Arousal (MMVA), a tri-modal encoder framework designed to capture emotional content across images, music, and musical captions. To support this framework, we expand the Image-Music-Emotion-Matching-Net (IMEMNet) dataset, creating IMEMNet-C which includes 24,756 images and 25,944 music clips with corresponding musical captions. We employ multimodal matching scores based on the continuous valence (emotional positivity) and arousal (emotional intensity) values. This continuous matching score allows for random sampling of image-music pairs during training by computing similarity scores from the valence-arousal values across different modalities. Consequently, the proposed approach achieves state-of-the-art performance in valence-arousal prediction tasks. Furthermore, the framework demonstrates its efficacy in various zeroshot tasks, highlighting the potential of valence and arousal predictions in downstream applications.

Daniela Hřebíčková

Ye Bai, Haonan Chen, Jitong Chen et al.

We introduce Seed-Music, a suite of music generation systems capable of producing high-quality music with fine-grained style control. Our unified framework leverages both auto-regressive language modeling and diffusion approaches to support two key music creation workflows: controlled music generation and post-production editing. For controlled music generation, our system enables vocal music generation with performance controls from multi-modal inputs, including style descriptions, audio references, musical scores, and voice prompts. For post-production editing, it offers interactive tools for editing lyrics and vocal melodies directly in the generated audio. We encourage readers to listen to demo audio examples at https://team.doubao.com/seed-music "https://team.doubao.com/seed-music".

Jinlong Zhu, Keigo Sakurai, Ren Togo et al.

We propose a novel symbolic music representation and Generative Adversarial Network (GAN) framework specially designed for symbolic multitrack music generation. The main theme of symbolic music generation primarily encompasses the preprocessing of music data and the implementation of a deep learning framework. Current techniques dedicated to symbolic music generation generally encounter two significant challenges: training data's lack of information about chords and scales and the requirement of specially designed model architecture adapted to the unique format of symbolic music representation. In this paper, we solve the above problems by introducing new symbolic music representation with MusicLang chord analysis model. We propose our MMT-BERT architecture adapting to the representation. To build a robust multitrack music generator, we fine-tune a pre-trained MusicBERT model to serve as the discriminator, and incorporate relativistic standard loss. This approach, supported by the in-depth understanding of symbolic music encoded within MusicBERT, fortifies the consonance and humanity of music generated by our method. Experimental results demonstrate the effectiveness of our approach which strictly follows the state-of-the-art methods.

C. Gramaglia, E. Gambaro, C. Vecchi et al.

BACKGROUND Effectiveness of music-based interventions (MI) on cancer patients' anxiety, depression, pain and quality of life (QoL) is a current research theme. MI are highly variable, making it challenging to compare studies. OBJECTIVE AND METHODS To summarize the evidence on MI in cancer patients, 40 studies were reviewed following the PRISMA statement. Studies were included if assessing at least one outcome among anxiety, depression, QoL and pain in patients aged ≥ 18, with an active oncological/onco-haematological diagnosis, participating to any kind of Music Therapy (MT), during/after surgery, chemotherapy or radiotherapy. RESULTS A positive effect of MI on the outcomes measured was supported. Greater reductions of anxiety and depression were observed in breast cancer patients. MI involving patients admitted to a hospital ward were less effective on QoL. CONCLUSION The increasing evidence about MI effectiveness, tolerability, feasibility and appreciation, supports the need of MI implementation in Oncology, Radiotherapy and Surgery wards, and promotion of knowledge among health operators.

Alfredo Raglio

The therapeutic use of music is frequently based on active interventions that directly involve the patient through a sonorous-music interaction with the music therapist. In contrast, approaches based on musical listening are characterized by a relationship aimed at promoting an introspective work and processing of one’s emotional experiences. Increasingly, the scientific literature has shown how even listening to music related to the patient’s personal tastes (preferred music listening) and by-passing the direct relationship with the patient, can produce therapeutic effects in different clinical settings. However, in many cases, a clear therapeutic rationale and specific application protocols are still lacking. The paper introduces a novel approach based on music listening: the Therapeutic Music Listening. This approach integrates the subjective component of listening (patient’s musical tastes) and structural and parametric characteristics of the music in relation to the therapeutic aims. The article defines theoretical-applicative bases as well as therapeutic and research perspectives of this music listening-based intervention.

Alvee Saluja, Vinay Goyal, Rajinder K Dhamija

Long-term use of dopaminergic therapy in Parkinson's disease (PD) is associated with reduction in efficacy and disabling dyskinesias. The current medical or surgical treatment modalities are ineffective for atypical parkinsonism syndromes. Hence, there is a need for holistic and cost-effective non-pharmacological interventions that act via multiple mechanisms to improve motor as well as non-motor symptoms among PD patients. Rehabilitation strategies focusing on multiple mechanisms can lead to improvement in certain symptoms among PD patients, which may be refractory to medical and surgical therapy. However, there is scanty literature available on the role of various rehabilitation strategies in patients with atypical parkinsonism patients. Multiple rehabilitation strategies such physiotherapy, aerobic exercises, strength/resistance exercises, treadmill training, cueing, dance and music, speech language therapy, occupational therapy, hydrotherapy, and martial arts have been found to improve motor as well as non-motor symptoms among PD patients. Newer modalities such as virtual-reality-based devices, exergaming, wearable sensors, and robotic prosthetic devices may be exciting future prospects in rehabilitation among patients with PD and atypical parkinsonian syndromes. This narrative review assessed and summarized the current evidence regarding the role of various rehabilitation strategies in PD and atypical parkinsonian syndromes. Furthermore, evidence regarding recent advancements in rehabilitation for patients with parkinsonism was highlighted. Despite the beneficial effect of rehabilitation in PD, there is still scanty literature available from India on rehabilitation strategies among PD patients. Larger prospective randomized control trials from India and other low- and middle-income countries, focusing on various rehabilitation strategies among PD patients, are an unmet need.

Mukasa Situma Wafula

Termite harvesting remains an important ritual and cultural activity in the Bukusu community of Western Kenya. Termites are a delicacy that people enjoy. Harvesting the termites takes different approaches as will be discussed in this article. The paper will, however, focus on one mode that makes use of a musical stimulus to attract the termites into a trap. In this article, I will venture into showing how this ritual of termite harvesting is an important part of the intangible cultural heritage of Babukusu. Further, I will seek to demonstrate how music can be central to interspecies communication. It is also envisaged that this article will contribute to the literature concerning ecomusicology, a new field of study that is in the process of developing definitions and terminology as well as conceptual understanding. This article drew data from field research I carried out in Bungoma County in 2017. Using ethnographic approaches, I interviewed participants during the harvesting rituals. Further data was gathered through participant observation. It is important to note that I come from this community and have over time participated in the ritual. Some of the information in this document is based on my position as an insider who has participated in this ritual over the years.

Seyed Mohammadreza Beladi

This article examines parts of the oral literature and music of Bushehr, a port city in southern Iran. There is a song in Bushehr's music that uses words like helleh (heːlle̞) and heliosa (heːlijosa), that have no meaning for the people of Bushehr. This paper suggests that the origin of these words goes back to Greek mythology and that they are the remains of hymns or spells recited in praise of Helios and other ancient gods. To this end, in addition to qualitative and field research, extensive historical studies were carried out, focusing on the Hellenistic period after the conquest of Iran by Alexander the Great. I suggest that although the evolution of music in Bushehr was influenced by the military domination of Greece through acculturation, the cultural background of Bushehr was not ineffective in accepting this. As a result, assimilation occurred, and some mythical elements of Greece were localised in Bushehr.

Sultan Almuhammadi, Abdullatif Alnajim, Mohammed Ayub

The Quick UDP Internet Connections (QUIC) protocol provides advantages over traditional TCP, but its encryption functionality reduces the visibility for operators into network traffic. Many studies deploy machine learning and deep learning algorithms on QUIC traffic classification. However, standalone machine learning models are subject to overfitting and poor predictability in complex network traffic environments. Deep learning on the other hand requires a huge dataset and intensive parameter fine-tuning. On the contrary, ensemble techniques provide reliability, better prediction, and robustness of the trained model, thereby reducing the chance of overfitting. In this paper, we approach the QUIC network traffic classification problem by utilizing five different ensemble machine learning techniques, namely: Random Forest, Extra Trees, Gradient Boosting Tree, Extreme Gradient Boosting Tree, and Light Gradient Boosting Model. We used the publicly available dataset with five different services such as Google Drive, YouTube, Google Docs, Google Search, and Google Music. The models were trained using a different number of features on different scenarios and evaluated using several performance metrics. The results show that Extreme Gradient Boosting Tree and Light Gradient Boosting Model outperform the other models and achieve one of the highest results among the state-of-the-art models found in the literature with a simpler model and features.

Ryosuke Sawata, Naoya Takahashi, Stefan Uhlich et al.

This paper presents the crossing scheme (X-scheme) for improving the performance of deep neural network (DNN)-based music source separation (MSS) with almost no increasing calculation cost. It consists of three components: (i) multi-domain loss (MDL), (ii) bridging operation, which couples the individual instrument networks, and (iii) combination loss (CL). MDL enables the taking advantage of the frequency- and time-domain representations of audio signals. We modify the target network, i.e., the network architecture of the original DNN-based MSS, by adding bridging paths for each output instrument to share their information. MDL is then applied to the combinations of the output sources as well as each independent source; hence, we called it CL. MDL and CL can easily be applied to many DNN-based separation methods as they are merely loss functions that are only used during training and do not affect the inference step. Bridging operation does not increase the number of learnable parameters in the network. Experimental results showed that the validity of Open-Unmix (UMX), densely connected dilated DenseNet (D3Net) and convolutional time-domain audio separation network (Conv-TasNet) extended with our X-scheme, respectively called X-UMX, X-D3Net and X-Conv-TasNet, by comparing them with their original versions. We also verified the effectiveness of X-scheme in a large-scale data regime, showing its generality with respect to data size. X-UMX Large (X-UMXL), which was trained on large-scale internal data and used in our experiments, is newly available at https://github.com/asteroid-team/asteroid/tree/master/egs/musdb18/X-UMX.

Siting Xu, Yolo Yunlong Tang, Feng Zheng

Launchpad is a musical instrument that allows users to create and perform music by pressing illuminated buttons. To assist and inspire the design of the Launchpad light effect, and provide a more accessible approach for beginners to create music visualization with this instrument, we proposed the LaunchpadGPT model to generate music visualization designs on Launchpad automatically. Based on the language model with excellent generation ability, our proposed LaunchpadGPT takes an audio piece of music as input and outputs the lighting effects of Launchpad-playing in the form of a video (Launchpad-playing video). We collect Launchpad-playing videos and process them to obtain music and corresponding video frame of Launchpad-playing as prompt-completion pairs, to train the language model. The experiment result shows the proposed method can create better music visualization than random generation methods and hold the potential for a broader range of music visualization applications. Our code is available at https://github.com/yunlong10/LaunchpadGPT/.

M. Leggieri, M. Thaut, L. Fornazzari et al.

Music interventions have been widely adopted as a potential non-pharmacological therapy for patients with Alzheimer’s disease (AD) to treat cognitive and/or behavioral symptoms of the disease. In spite of the prevalence of such therapies, evidence for their effectiveness report mixed results in the literature. The purpose of this narrative review is to investigate the effectiveness of various intervention strategies (music therapy vs. music listening techniques) and music type used in the intervention (individualized vs. non-individualized music) on cognitive and behavioral outcomes for persons with AD. Databases were searched for studies using either active music therapy or music listening techniques over the last 10 years. These studies were in English, included persons with AD dementia, and whose protocol gathered pre- and post-intervention outcome measures. We initially identified 206 papers which were then reduced to 167 after removing duplicates. Further review yielded 13 papers which were extensively reviewed, resulting in a final sample of six papers. Our analysis of these papers suggested that, regardless of the music intervention approach, individualized music regimens provided the best outcomes for the patient. Furthermore, music listening may act as a relaxation technique and therefore provide a long-term impact for the patient, while active music therapy may acts to engage participants through social interaction and provide acute benefits. Our findings suggest that music techniques can be utilized in various ways to improve behavior and cognition.

Chenyan Dai, Raja Iskandar bin Raja Halid, Kanit Sripaoraya

The spread of Cantonese music in Malaysia and its impact on the diversification of Malaysian music education is in the spotlight. Cantonese music has injected new momentum into the development of Malaysian music education and has driven the development of Malaysian music into diversity. The interview method was used to visit the Malaysian Chinese Association to understand how the early Chinese community spread Cantonese music in Malaysia; and then uses the historical method to explore the contribution of Cantonese music development to Malaysian music education by comparing the available literature. The results of the study show that Cantonese music contributed to the shift of music education in Malaysia from the top to the bottom of society, making the reason for the change of focus of education in Malaysia. Educational resources began to reach out to the whole society, which stirred up the desire for music education among the lower class in Malaysia. At a later stage of development, Cantonese music in Malaysia gradually merged with the local music culture. From no orchestra in elementary and advanced education grew to more than 106 Chinese music teams. From individual immigrants to more than 17 Chinese congregations. From having no major music ensemble competition to a Chinese band competition once every two or three years. Cantonese music has not only expanded the scope of music education in Malaysia but also injected new musical and cultural vitality and enriched the methods and forms of music education. The development of music education in Malaysia has also indirectly stimulated the development of Cantonese music, with the emergence of school-level Chinese orchestras and Chinese music competitions. Malaysian music education has developed online music education on the Internet, and the music education system has gradually become globalized.

John E. Lothes II, Sara Matney, Zayne Naseer

Background: Research shows that mindfulness interventions for test anxiety in a college student population are beneficial (Lothes, Mochrie, Wilson, & Hakan, 2021). This study expands on the existing literature by examining how distance learning mindfulness practices may affect anxiety in college students. Aim: This study assessed the effects of online mindfulness practices over a five-week period on test anxiety in college students. Method: Participants included 31 college students that were randomly assigned to either a sitting meditation or music meditation condition. The two groups were also split in half to add a wait list control condition. A weekly schedule of mindfulness practices was given to participants to complete on their own. Results: Participants in the sitting meditation condition showed significant within-group reductions in test anxiety, overall anxiety, and mindfulness from start to finish. The music meditation group showed no changes in test anxiety. However, overall anxiety showed decreases in scores, and overall mindfulness did show significant increases for this group. Conclusion: Mindfulness may play a role in the reduction of anxiety and test anxiety. Further research is needed to more definitively assess how music meditation may impact anxiety.