Hasil untuk "Music and books on Music"

Luis José Roncagliolo Bonicelli

Uno de los capítulos más llamativos en la historia de la música orquestal peruana durante el siglo XX, corresponde al concurso de composición de una sinfonía para conmemorar el Sesquicentenario de las Batallas de Junín y Ayacucho, en 1974. Este certamen fue convocado por el Ejército del Perú en el marco del gobierno militar de turno, y formó parte de una serie de acciones llevadas a cabo en recuerdo de aquellas batallas decisivas para la independencia de los países sudamericanos. En el presente artículo se explora el contexto del concurso, las dificultades para reconstruirlo debido al carácter cerrado que tuvo durante casi todo su desarrollo, las diversas relaciones entre los compositores y ciertas variables que podrían haber incidido directamente en las obras resultantes, así como la noción de lo monumental, que favoreció las conmemoraciones de aquel entonces, y que se aprecia también en las composiciones premiadas, especialmente en la obra ganadora.

Jianfu Li

This article presents a discussion about Xiangtong Xi (香童戏), a traditional musical theatrical form associated with the Baoshan area of China’s Yunnan province. Xiangtong Xi drama originated from the folk religious and mystical rites of the southwestern regions of China. It organically combines elements such as singing, recitation, acting and martial arts techniques that are characteristic of the musical culture of the region. This genre has its own cult music and traditional performance style. At the same time, supporting and preserving the traditions of their art, Xiangtong Xi artists throughout the history of its existence have developed and continue to develop Xiangtong Xi music by studying the singing melodies and musical styles of other cultures, musical genres and movements and introducing their elements into their performances. The basis for such borrowings is primarily local folk music and songs, as well as other traditional musical genres of the region. Keywords: Xiangtong Xi, musical drama, ritual music, religious music, Prince’s Chant, Even Chant, Universal Chant, Chant of the Black God, plague god’s chant, percussion instruments For citation: Li Jianfu (2025). Traditional Regional Features in Xiangtong Xi Musical Drama. Contemporary Musicology, 9(2), 134–150. https://doi.org/10.56620/2587-9731-2025-2-134-150

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.

Hadi Susanto, Andre Indrawan

Dambus merupakan alat musik tradisional khas Bangka Belitung yang menunjukkan perkembangan signifikan baik dari segi kualitas maupun kuantitas. Secara kualitas, banyak perajin Dambus tersebar di seluruh Provinsi Kepulauan Bangka Belitung yang memproduksi instrumen ini hingga dipasarkan ke luar negeri. Sementara itu, secara kuantitas, jumlah pembuat, pemain, komunitas, dan penikmat musik Dambus juga terus meningkat. Namun, perkembangan ini belum diimbangi dengan sistem pelestarian yang memadai. Selama ini, pembelajaran Dambus dilakukan secara lisan, seperti halnya tradisi musik tradisional pada umumnya, sehingga berpotensi punah seiring waktu. Penelitian ini bertujuan merancang sistem pembelajaran Dambus berbasis notasi tertulis sebagai upaya pelestarian dan dokumentasi. Model yang dikembangkan mengadaptasi metode pembelajaran gitar, namun disesuaikan dengan karakteristik khas instrumen Dambus. Rancangan pembelajaran disusun secara bertahap, dimulai dari teknik dasar, notasi, hingga latihan-latihan fundamental. Diharapkan, sistem pembelajaran berbasis notasi ini dapat memperkuat eksistensi musik Dambus dan mendorong lahirnya karya-karya baru yang terdokumentasi dengan baik. Developing a Dambus Learning Model Based on Guitar Notation for the Preservation of Bangka Traditional Music Abstract Dambus is a traditional musical instrument native to the Bangka Belitung Islands that has shown significant development in both quality and quantity. In terms of quality, numerous Dambus craftsmen are spread across the Bangka Belitung Province, producing instruments that are even marketed internationally. Quantitatively, the number of makers, performers, communities, and enthusiasts of Dambus music continues to grow. However, this progress has not been matched by an adequate preservation system. Until now, Dambus learning has been conducted orally, as is common in traditional music practices, making it vulnerable to extinction over time. This study aims to design a written notation–based learning system for Dambus as a means of preservation and documentation. The model developed adapts guitar teaching methods but is modified to suit the distinctive characteristics of the Dambus instrument. The instructional framework is structured gradually, beginning with basic techniques, notation, and fundamental exercises. It is expected that this notation-based learning system will help strengthen the existence of Dambus music and encourage the creation of new, well-documented musical works. Keywords:  Traditional music of Bangka; instrumental music pedagogy; music notation system; Dambus

Олег Степанович Смоляк, Богдан Остапович Водяний, Ірина Вікторівна Романюк

У статті представлено новітні аналітичні алгоритми щодо реального музичного тексту як Тексту культури, що розглядається в ролі його структурно-семантичного інваріанту як засобу комунікації. Методи дослідження – структурно-герменевтичний, моделювання, функціональний. Результати дослідження формулюються на основі доведення того, що конструкти цього інваріанту володіють синергічною природою – тісною взаємодією та наскрізністю вияву. Задля унаочнення цієї взаємодії пропонується модель архітектоніки Світу музики як звукоінтонаційного середовища та мистецтва інтонованого смислу. Це – концентрично розташовані площини, які є рівнями його побудови. А саме: музичні лексеми (осереддя моделі); інтонаційний рельєф тематичного матеріалу; тип композиційно-драматургічної логіки; інваріант жанрової форми; інваріант стилю; історичний тип культури у вимірах «духовної ситуації часу»; історично актуальна світоглядна парадигма; інтонаційний континуум. Наголосимо, що поміж названими конструктами моделі існують взаємозумовлюючі звʼязки, у яких щоразу «просвічує» слід інших конструктів. Тому велике значення має як доцентровий, так і відцентровий рух від осереддя моделі до її замикаючого «поля», який фактично пронизує усю модель ідеєю щодо інтонаційної природи Світу музики в цілому. Практичну доцільність розробленої моделі забезпечено новітніми поняттями та категоріями сучасного систематичного музикознавства зразка «інтонаційна модель» (В. Москаленко), «інтонаційний образ світу» (Ю. Чекан), «типологія композиційно-драматургічного структурування» (Н. Горюхіна), «семантика жанрової форми» (М. Арановський, Т. Симонова); «металогіка стилю» (О. Завʼялова, М. Ярко), «психоаналітичні виміри індивідуального композиторського стилю» (М. Ярко), «національно-культурна ідентичність у матрицях етнічної та національної форм ідентичності» (М. Ярко), «алюзійний спосіб розвитку національного стилю» (М. Ярко), «українська академічна пісня» (Б. Водяний, Т. Задорожна) та ін. Висновкові судження щодо проведеного дослідження та його практичне значення тісно повʼязані з музикознавчою та музично-освітньою практикою: відомості щодо архітектоніки Світу музики та структурно-семантичного інваріанту музичного тексту як Тексту культури здатні забезпечувати високу міру праксеологічного (раціонально-логічного й ефективного) та евристичного (творчого) потенціалу як дослідницької, так і навчально-освітньої практики. Зокрема, перспективи подальших досліджень в обраному напрямі бачаться у звʼязку з проекціями розвитку когнітивної експансії свідомості в намірі глибокого пізнання духовного світу мистецької творчості.

Yulia S. Veksler

The article highlights a high-profile project by the Bern Academy of Arts to bring back into musical life one of the key works in the history of 20th-century Swiss music — Othmar Schoeck’s opera Das Schloß Dürande (1941). For many decades, despite its manifest musical merits, the performance of this composition seemed absolutely impossible due to the political overtones with which it is associated. Various “interpretive restoration” strategies were aimed at creating a new version of the opera. In the first place, the libretto, which was created by the Nazi writer Hermann Burte and based on the novella of the same name by the 19th-century German romantic author Joseph Eichendorff, underwent significant revision. The rather low literary level of the original libretto, which employed a large number of ideological clichés ad slogans, required the replacement of more than half of the text, essentially involving its rewriting based on the appropriate verse texts written by Eichendorff. The changes also affected the vocal part. In addition, a careful study of historical documents made it possible to clarify the circumstances of the opera’s premiere, which took place in Nazi Berlin in 1943. After a mere four performances, the opera was removed at the request of the Third Reich ideologist, Hermann Göring. New biographical information has also more fully revealed the position of Schoeck, who was not a supporter of National Socialism. Considering that “being Swiss” meant adopting a scrupulous attitude of “neutrality”, the composer collaborated with the Nazis for career reasons. The result of many years of work on the project was the performance of the updated opera Daß Schloß Dürande at the Meiningen Theatre in 2019. It didn’t convince everyone. However, the determining factor in assessing the opera was not so much the quality of the music and libretto, but rather the problematic history of its creation and reception in an ideological context. Thus, even in its new “denazified” version, Das Schloß Dürande remains closely connected with the past.

Bogdan-Sorin Ilies, Camelia-Florina Andor

While being different forms of art, literature and music are similar in being able to convey symbolism, narrative and emotion. This paper explores the design and implementation of a music recommendation system in the context of a book and reading progress tracking web application. At the center of this work lies the question: How well can artificial intelligence find similarities between books and musical pieces and establish connections between them based on their symbolism? The main objective is to provide an answer to this question, by leveraging natural language processing algorithms. Numerous such algorithms have been implemented in music streaming applications, with the goal of recommending songs based on the user's listening preferences. However, the topic of music recommendations based on other arts or abstract human interests using artificial intelligence remains only briefly touched. This research aims to explore and extend this field, by employing techniques meant to provide relevant music suggestions stemming from literary tastes and to demonstrate the capacity of an artificial intelligence model to make accurate recommendations, by establishing connections between the semantic meanings and conveyed feelings of book snippets and song lyrics. Lastly, this work intends to contribute to the field of natural language processing in artificial intelligence, by bridging the gap between two prominent cultural arts in this day and age, by building an exploration base for correlating music with other forms of art.

Kiara Hosie

How do audiences come to understand a character who appears to lack a discrete performed identity? This paper explores how, in performance, music and theories of magic and reader response interact to create the identity of the musical spirit, Ariel, from William Shakespeare’s (1564-1616) The Tempest (1611). To facilitate this exploration, I outline Ariel’s characterisation across six productions from the Renaissance, Restoration, and modern-day on two levels: textual (concerning how culturally-bound theories of magic and gender affect interpretations of the play’s script), and performed (concerning practical decisions such gender casting, voice type, and visual design). Across both the textual and performed levels, I emphasise the roles of socio-cultural contexts and resultant audience perceptions in informing Ariel’s identity in each production, ultimately proposing that while Ariel’s textual identity as a genderless spirit remains relatively stable from the Renaissance to the modern-day, each production of The Tempest creates a new performed identity for the character through dynamic interactions between culture, history, directors, performers, and audiences.

Seta Kürkçüoğlu, Nesibe Özgül Turgay, M. Akif Kılıç et al.

In this study, a preliminary comparative study was conducted for the first time using the DoctorVox device by instructor–performer participants using two different formant patterns in Turkish and Western music. The participants used the DoctorVox device before recordings to practice the selected tonal exercises ascending and descending; they recorded glissando exercises and [a], [e], [i], [o] vocals in a constant studio setting at Week 0 at the start of the study and Week 8 at the end of the study. The data obtained from the measurements were evaluated in the Customized Praat Program in line with the determined parameters, and thus, the results were revealed. In this study, the measured values of fundamental frequency, jitter, shimmer, harmonic noise ratio, pitch values, maximum phonation time, and voice range improved in all objective measurements. The subjective measurement outcomes indicated that participants’ vocal and breathing health was good, their conditions improved, voices warmed rapidly, felt comfortable in high notes, physical and mental bonding grew gradually, and their confidence increased. In addition, participants’ motivation and professional goals improved, such as delivering performances and adding new pieces to their repertoire. Because of the athletic achievements obtained using the selected tonal vocal exercises as a vocal training method in the study, it is believed that it will help to eliminate existing negative thoughts about the use of (Western) vocal exercises that are methodologically supported by scientific data and will contribute to the present literature for vocal studies.

Oleg GARAZ

Is it possible to communicate through music? Does the music communicate something in particular? Is music like the message in a bottle – the meaning wrapped in the envelope of a form? Who would be the recipient of the „musical message” in this case – one, many, all of humanity, as in the IV parts of Beethoven’s Ninth Symphony? Or maybe just Captain Grant’s children? And how pertinent is the extrapolation of notional-discursive schema and logic to music as Mattheson did in Der Vollkommene Kapellmeister? Because this phrase – the message of music – immediately refers to both the „suggestive” neutrality of musical sounds and the „emotional” irrelevance of the relationships between them. Sounds are just sounds. Is a chord the analogy of the word, the melody the analogy of the phrase, and a whole articulation the substitute of a speech? Is music a language? Or, indeed, being both sonorous, but also processual and symbolic, just like spoken language, music does not connote in the same way. And if the language has prescribed references, then music does not. A chord, a melody, let alone a counterpoint, have no predetermined meaning, not even one resembling a notional one, even after the performance is over. Should the composer first be a very good connoisseur of human emotional behavior rather than a very good musician? Or, perhaps, a simple postman, as in the famous song of the Beatles?

Jonathan Knott

In July 1967 the Beatles were making plans to buy a Greek island, and visited the country with this aim in mind. At the time, negative international opinion regarding the military dictatorship that had recently come to power in Greece was contributing to a decline in the country’s tourism sector. Several credible accounts suggest that the Beatles’ visit was used to generate publicity in the hope of encouraging tourism to Greece. But if so, the details of how such an initiative might have come about have remained unclear. In this article I examine the evidence for the group’s activity in Greece, as well as relevant actions from other individuals and the wider historical context. Doing so highlights a range of political connections and dimensions to the events that offer a new perspective on the Beatles and may help us better understand the interactions between politics, celebrity and culture at the time. This article was published open access under a CC BY licence: https://creativecommons.org/licences/by/4.0.

Charlene Ryan, Hélène Boucher, Gina Ryan

Parents play a variety of important roles in their children's musical development. However, whether they impact upon children's music performance education and experience has only begun to be considered. The current study sought to examine whether student perception of parent involvement in music and performance education is related to their experience of music performance anxiety. Sixty-two piano students aged 11 to 17 completed a questionnaire regarding their piano studies, their parents’ involvement in them, and their parents’ prior music education. They also completed measures of performance anxiety and self-esteem. Results indicated that parents’ prior music education was significantly associated with performance anxiety in their children. Participant age, self-esteem, and practice time were also significant variables. Measures of parent involvement in music studies and parent response to weak performances were not found to be significantly related to performance anxiety scores. Implications of these findings and directions for furthering this line of research are discussed.

Ana Llorens, Federico Simonetta, Martín Serrano et al.

In this work, we introduce musif, a Python package that facilitates the automatic extraction of features from symbolic music scores. The package includes the implementation of a large number of features, which have been developed by a team of experts in musicology, music theory, statistics, and computer science. Additionally, the package allows for the easy creation of custom features using commonly available Python libraries. musif is primarily geared towards processing high-quality musicological data encoded in MusicXML format, but also supports other formats commonly used in music information retrieval tasks, including MIDI, MEI, Kern, and others. We provide comprehensive documentation and tutorials to aid in the extension of the framework and to facilitate the introduction of new and inexperienced users to its usage.

Huan Zhang, Emmanouil Karystinaios, Simon Dixon et al.

Music Information Retrieval (MIR) has seen a recent surge in deep learning-based approaches, which often involve encoding symbolic music (i.e., music represented in terms of discrete note events) in an image-like or language like fashion. However, symbolic music is neither an image nor a sentence, and research in the symbolic domain lacks a comprehensive overview of the different available representations. In this paper, we investigate matrix (piano roll), sequence, and graph representations and their corresponding neural architectures, in combination with symbolic scores and performances on three piece-level classification tasks. We also introduce a novel graph representation for symbolic performances and explore the capability of graph representations in global classification tasks. Our systematic evaluation shows advantages and limitations of each input representation. Our results suggest that the graph representation, as the newest and least explored among the three approaches, exhibits promising performance, while being more light-weight in training.

Giorgio Fabbro, Stefan Uhlich, Chieh-Hsin Lai et al.

This paper summarizes the music demixing (MDX) track of the Sound Demixing Challenge (SDX'23). We provide a summary of the challenge setup and introduce the task of robust music source separation (MSS), i.e., training MSS models in the presence of errors in the training data. We propose a formalization of the errors that can occur in the design of a training dataset for MSS systems and introduce two new datasets that simulate such errors: SDXDB23_LabelNoise and SDXDB23_Bleeding. We describe the methods that achieved the highest scores in the competition. Moreover, we present a direct comparison with the previous edition of the challenge (the Music Demixing Challenge 2021): the best performing system achieved an improvement of over 1.6dB in signal-to-distortion ratio over the winner of the previous competition, when evaluated on MDXDB21. Besides relying on the signal-to-distortion ratio as objective metric, we also performed a listening test with renowned producers and musicians to study the perceptual quality of the systems and report here the results. Finally, we provide our insights into the organization of the competition and our prospects for future editions.

Xingjian Du, Zhesong Yu, Jiaju Lin et al.

Music tagging is a task to predict the tags of music recordings. However, previous music tagging research primarily focuses on close-set music tagging tasks which can not be generalized to new tags. In this work, we propose a zero-shot music tagging system modeled by a joint music and language attention (JMLA) model to address the open-set music tagging problem. The JMLA model consists of an audio encoder modeled by a pretrained masked autoencoder and a decoder modeled by a Falcon7B. We introduce preceiver resampler to convert arbitrary length audio into fixed length embeddings. We introduce dense attention connections between encoder and decoder layers to improve the information flow between the encoder and decoder layers. We collect a large-scale music and description dataset from the internet. We propose to use ChatGPT to convert the raw descriptions into formalized and diverse descriptions to train the JMLA models. Our proposed JMLA system achieves a zero-shot audio tagging accuracy of $ 64.82\% $ on the GTZAN dataset, outperforming previous zero-shot systems and achieves comparable results to previous systems on the FMA and the MagnaTagATune datasets.

Axel Marmoret, Jérémy E. Cohen, Frédéric Bimbot

Music Structure Analysis (MSA) is a Music Information Retrieval task consisting of representing a song in a simplified, organized manner by breaking it down into sections typically corresponding to ``chorus'', ``verse'', ``solo'', etc. In this work, we extend an MSA algorithm called the Correlation Block-Matching (CBM) algorithm introduced by (Marmoret et al., 2020, 2022b). The CBM algorithm is a dynamic programming algorithm that segments self-similarity matrices, which are a standard description used in MSA and in numerous other applications. In this work, self-similarity matrices are computed from the feature representation of an audio signal and time is sampled at the bar-scale. This study examines three different standard similarity functions for the computation of self-similarity matrices. Results show that, in optimal conditions, the proposed algorithm achieves a level of performance which is competitive with supervised state-of-the-art methods while only requiring knowledge of bar positions. In addition, the algorithm is made open-source and is highly customizable.

Pedro Sarmento, Adarsh Kumar, Yu-Hua Chen et al.

Recently, symbolic music generation with deep learning techniques has witnessed steady improvements. Most works on this topic focus on MIDI representations, but less attention has been paid to symbolic music generation using guitar tablatures (tabs) which can be used to encode multiple instruments. Tabs include information on expressive techniques and fingerings for fretted string instruments in addition to rhythm and pitch. In this work, we use the DadaGP dataset for guitar tab music generation, a corpus of over 26k songs in GuitarPro and token formats. We introduce methods to condition a Transformer-XL deep learning model to generate guitar tabs (GTR-CTRL) based on desired instrumentation (inst-CTRL) and genre (genre-CTRL). Special control tokens are appended at the beginning of each song in the training corpus. We assess the performance of the model with and without conditioning. We propose instrument presence metrics to assess the inst-CTRL model's response to a given instrumentation prompt. We trained a BERT model for downstream genre classification and used it to assess the results obtained with the genre-CTRL model. Statistical analyses evidence significant differences between the conditioned and unconditioned models. Overall, results indicate that the GTR-CTRL methods provide more flexibility and control for guitar-focused symbolic music generation than an unconditioned model.