Song Characteristics Research Articles

2015 개정 및 2022 개정 교육과정에 따른 '즐거운 생활' 교육과정과 교과서의 음악 학습 내용 비교

As the 2022 revised curriculum was implemented, significant changes emerged in the content structure and textbook system of the elementary school integrated curriculum. This study aims to investigate how the "Pleasant Life" curriculum and the music learning content in elementary school textbooks impact music education. To this end, the study first compares the characteristics of the "Joyful Life" curriculum in the 2015 and 2022 revised curriculum. Second, the study analyzes in detail the characteristics of songs and music learning activities included in the integrated textbooks of both periods. Third, it identifies the challenges faced in music education for first and second-grade students within the integrated curriculum system and proposes improvement strategies to address these issues. The findings reveal that while the 2022 revised curriculum emphasizes teacher and student autonomy, it does not adequately support foundational music learning. Specifically, as the difficulty of songs in the textbooks increased and music activities decreased, students lacked sufficient opportunities for meaningful musical experiences. Therefore, to ensure effective music education for lower grades, music instruction should be delivered separately from integrated subjects, with a more systematic and developmentally appropriate approach. Additionally, there is a need to present musical scores in varied formats and include easier songs in textbooks. Improvements should also focus on designing music learning activities that align with the developmental stages of young learners, making musical concepts easier to understand and learn systematically.

An Analysis of Traditional and Contemporary Children’s Songs With Considerations for Music Therapy Practice

Abstract Children’s songs include a diverse collection of traditional and contemporary songs. (Yinger and Springer [2016]. Analyzing recommended songs for older adult populations through linguistic and musical inquiry. Music Therapy Perspectives 34, 116–125. https://doi.org/10.1093/mtp/miu048) analyzed musical and textual features of songs used by music therapists with older adults; however, studies on children’s songs in music therapy have not included musical and textual features analysis. Our purpose with this study was to analyze the musical and textual features of a sample of 20 traditional and 20 contemporary predominantly U.S. children’s songs and consider applications for music therapy. Text information was collected, including total and unique words, the song topic, and potential applications. Musical information was collected, including form, melodic range, and harmonic/chordal structure. Findings included that the traditional songs were strophic, had fewer overall words, were harmonized with three chords or fewer, and had melodic ranges of five to seven notes. By contrast, contemporary children’s songs used complex song forms, had more words, were harmonized with more than three chords, and had melodic ranges of eight or more notes. Song topics and applications had similar codes across the song types. A music therapist may apply traditional songs in clinical work, where a simpler musical structure and fewer words support the client’s needs. Likewise, a music therapist may apply contemporary songs for greater musical complexity and more vocabulary. Future studies of children’s songs in music therapy could include an analysis of music therapists’ composed songs and songs used by music therapists who work with young children.

Praising Heroes with Superior Morality in Hausa Songs: A Treatise of Courage

The aim of this article is to examine the role played by Gobir’s courage in protecting the city-state and the significance of superior morality in dousing problems that courage might cause and its importance to spectator(s) as portrayed by the lyrics of the song, Bahagon Gulbi. The song features some qualities of war and is a court song, which consists of courage and manliness and the immemorial character of Gobirawa time. Using the purposive sampling strategy, thirteen stanzas (13) were selected from the song while examining courage and superior morality. The findings revealed that the lyrical structures of the song motivated Gobirawa’s confidence, courage and wisdom of their heroes accordingly. In other words, the singer’s superior morality guides his courage to benefit from wisdom in praising heroes to go to war and defend the city-state and not be afraid of nothing but believe in Allah because one may die even at home. Akwara’s sermon to Gobirawa has faith in dying while protecting the city-state as a noble death and respecting superior authority as superior morality. With this belief in mind, he encourages his master to pay homage to Sarkin Musulmi Muhammadu Tambari (1924-1930) for peace and harmony to reign significantly between the two states. Succinctly, the song celebrates, encourages and appreciates Gobirawa to reinvent while learning from the past.

Agonistic song rate positively correlates with male breeding success and avian malaria infection in Acrocephalus paludicola (Aquatic Warbler), a promiscuous songbird with female-only parental care

Abstract The link between male song and reproductive success has been explored at length in socially monogamous birds, but results were inconsistent and under-represented socially non-monogamous species with uniparental care. Here, we evaluated whether metrics of male song in Acrocephalus paludicola (Aquatic Warbler), a promiscuous songbird with female-only care and large repertoires, are associated with fitness- and quality-related traits. We showed that the number of 9-day-old nestlings fathered and probability of avian malaria infection increased with the rate of agonistic song, produced in male–male interactions, and that male-scaled mass index (proxy for energy reserves) positively correlated with the repertoire size. The male breeding success was not explained by repertoire size and song duty cycle. None of the song variables clearly explained the male return rate or change in the tarsus length (proxy for structural body size) and scaled mass index of the fathered chicks between days 2 and 9 post-hatch. No other relationships between the song characteristics and the inbreeding coefficient, scaled mass index, wing-length and Trypanosoma infection status of the males were supported, and Plasmodium infection was unrelated to the song duty cycle and repertoire size. We conclude that in male A. paludicola the repertoire size could be a signal of early developmental stress or current body condition, and the agonistic song rate could be shaped by sexual selection and signal to females a genetic makeup that enhances survival upon infection by Plasmodium.

Song determined by phylogeny and body mass in two differently constrained groups of birds: manakins and cardinals

The songs of birds are complex signals that may have several functions and vary widely among species. Different ecological, behavioural and morphological factors, as well as phylogeny, have been associated as predictors of the evolution of song structure. However, the importance of differences in development, despite their relevance, has seldom been considered. Here, we analysed the evolution of song in two families of songbirds that differ in song development, manakins (suboscines) and cardinals (oscines), with their phylogeny, morphology, and ecology. Our results show that song characteristics had higher phylogenetic signal in cardinals than in manakins, suggesting higher evolutionary lability in the suboscines. Body mass was the main predictor of song parameters in manakins, and together with habitat type, had a major effect on cardinals’ song structure. Precipitation and altitude were also associated with some song characteristics in cardinals. Our results bring unexpected insights into birdsong evolution, in which non-learners (manakins) revealed greater evolutionary lability than song learners (cardinals).

Alternative payment models in the music streaming market: A comparative approach based on stream-level data

Music streaming platforms’ models for sharing revenues with content providers have been the subject of intense debate for nearly a decade. The dominating model involves pooling platform revenues and allocating these funds to songs based on a song's share of the total number of platform streams. Since this model has several controversial consequences, alternative models have been proposed. This paper uses a novel approach to assess the two most discussed models – the “user-centric” and the “artist-centric”. Our approach relies on a unique data set of 154,505 streaming platform users (890 million streams) and simulates how a large-scale implementation of these models may reallocate revenues across different songs and rightsholders. We disentangle the static effects of a transition to a “user-centric” or an “artist-centric” model across each of six different song characteristics. We then compare the results of the two models. We show that contrary to its objective, an artist-centric payment system does not significantly improve remuneration to professional artists while the user-centric payment system would generate more significant changes in revenue reallocation, mainly at the expense of Rap & Hip-hop songs, superstars and new releases. Finally, we analyze the positions of the various stakeholders with regard to each of them.

Efficient Exploration and Exploitation for Sequential Music Recommendation

Music streaming services heavily rely upon recommender systems to acquire, engage, and retain users. One notable component of these services are playlists, which can be dynamically generated in a sequential manner based on the user’s feedback during a listening session. Online learning to rank approaches have recently been shown effective at leveraging such feedback to learn users’ preferences in the space of song features. Nevertheless, these approaches can suffer from slow convergence as a result of their random exploration component and their session-agnostic exploitation component. To overcome these limitations, we propose a novel online learning to rank approach which efficiently explores the space of candidate recommendation models by restricting itself to the orthogonal complement of the subspace of previous underperforming exploration directions. Moreover, we propose a session-aware exploitation component which leverages the momentum of the current best model during updates. Our thorough evaluation using simulated listening sessions from two large Last.fm datasets demonstrates substantial improvements over state-of-the-art approaches in terms of early-stage performance, which results in an improved user experience during online learning. In addition, we demonstrate that long-term convergence can be further enhanced by adaptively relaxing exploration constraints along the way.

Orchard bird song recognition based on multi-view multi-level contrastive learning

In the harvest season, orchards are frequently plagued by birds, and thus significant fruit pecking can adversely affect both the fruit quality and yield. Recognizing bird songs is crucial for preventing damage caused by orchard birds because it can provide the basis for subsequent bird repellent efforts. However, the extensive effort required to annotate sound samples poses a significant challenge for supervised deep learning. In this paper, we propose a self-supervised multi-view learning framework based on multi-level contrasting (MV-MLC) for bird song recognition, which utilizes both time and spectrogram views as inputs. This framework leverages MLC to automatically learn representations from unlabeled data and a multi-scale feature extraction (MSFE) backbone network is employed to capture the temporal features of bird songs at different scales. The time-spectrogram consistency task in MLC learning facilitates semantic-level information exchange across multi-views, while the hierarchical contrastive learning task captures granularity-level information, thereby resulting in more robust contextual representations. In addition, embedding the shuffle attention module in MSFE facilitates mining of the spatial and channel dependencies of bird song features to further enhance the representation of features by the multi-scale network. We conducted extensive experiments using our self-built 10-class bird song data set (Orchard-birds) and the publicly available Birdsdata and Powdermill data sets. The experimental results demonstrated that MV-MLC performed better than state-of-the-art self-supervised models. In particular, MV-MLC obtained outstanding performance even with a small proportion of labeled data. The recognition accuracies based on the Orchard-birds and Birdsdata data sets were 99.40% and 92.67%, respectively, with macro F1-scores of 99.40% and 92.61%.

Morphological Comparison of Larynx, Syrinx and Trachea of Some Wild Birds

The presence of both the larynx and syrinx in the respiratory system, the trachea consisting of long and complete cartilage rings, and the presence of air sacs are some of the important features that distinguish birds from mammals. There have been many studies on the larynx, trachea and syrinx as they are the distinguishing features of song and bird vocalizations in many avian species. In the present study, the purpose was to demonstrate the morphological structures of the larynx, trachea and syrinx, which is a sound organ, pigeon, sparrowhawk, falcon, eagle, goose, crow and stork. A total of 48 specimens, were used in the study. The materials were stained with methylene blue for better observation and counting of the tracheal rings. The staining procedure was performed by soaking the materials in alcohol, methylene blue solution and alcohol solutions of different concentrations, respectively. It was observed that the tracheal cartilages were a complete ring in all study species, but there were differences in tracheal length, number of cartilages and dorsoventral flattening. Syrinx was found to be tracheal type in storks and tracheobronchial type in others. As a result, the similarities and differences of the data obtained from pigeon, falcon, sparrowhawk, eagle, crow, goose and stork on larynx, trachea and syrinx due to different hunting, singing and vocal characteristics were revealed.

Predicting song popularity in the digital age through Spotifys data

This study delves into predicting song popularity on Spotify by analyzing a dataset of song features from 1986 to 2022. Using linear regression, this paper examines the influence of audio characteristics such as energy, danceability, speechiness, duration, and mode, alongside the year of release. The findings indicate that danceability, more recent release years, and longer track duration are positively associated with higher popularity levels. Conversely, songs in minor keys are more favored than those in major keys. These results highlight the significance of both intrinsic musical qualities and evolving listener preferences over time. The model's robustness is ensured through comprehensive diagnostic tests that validate the assumptions of linearity, normality, and homoscedasticity, confirming the predictive reliability of the identified factors. This research not only enhances the understanding of the dynamics driving music popularity but also provides valuable insights for artists and producers aiming to optimize their music for digital platforms. By focusing on the critical elements that resonate with contemporary audiences, stakeholders can better strategize their music releases to maximize listener engagement and success on streaming platforms.

A novel similarity measure SF-IPF for CBKNN with implicit feedback data

PurposeThe increasing popularity of music streaming services also increases the need to customize the services for each user to attract and retain customers. Most of the music streaming services will not have explicit ratings for songs; they will have only implicit feedback data, i.e user listening history. For efficient music recommendation, the preferences of the users have to be infered, which is a challenging task.Design/methodology/approachPreferences of the users can be identified from the users' listening history. In this paper, a hybrid music recommendation system is proposed that infers features from user's implicit feedback and uses the hybrid of content-based and collaborative filtering method to recommend songs. A Content Boosted K-Nearest Neighbours (CBKNN) filtering technique was proposed, which used the users' listening history, popularity of songs, song features, and songs of similar interested users for recommending songs. The song features are taken as content features. Song Frequency–Inverse Popularity Frequency (SF-IPF) metric is proposed to find the similarity among the neighbours in collaborative filtering. Million Song Dataset and Echo Nest Taste Profile Subset are used as data sets.FindingsThe proposed CBKNN technique with SF-IPF similarity measure to identify similar interest neighbours performs better than other machine learning techniques like linear regression, decision trees, random forest, support vector machines, XGboost and Adaboost. The performance of proposed SF-IPF was tested with other similarity metrics like Pearson and Cosine similarity measures, in which SF-IPF results in better performance.Originality/valueThis method was devised to infer the user preferences from the implicit feedback data and it is converted as rating preferences. The importance of adding content features with collaborative information is analysed in hybrid filtering. A new similarity metric SF-IPF is formulated to identify the similarity between the users in collaborative filtering.

Analysis of the characteristics and condition of folk songs of the north of Shaanxi province and their translations into Russian

The aim is to substantiate and analyse the features of folk songs of the north of Shaanxi Province (China) within the framework of the concepts of linguistic picture of the world and linguistic realities and to identify the qualitative indicators of their translation into Russian. In order to achieve this goal, the main task was to find a translation way to convey the content of linguistic realities within the framework of understanding the linguistic picture of the world and thus ensure the quality of their translation into Russian. In addition, we had to solve a number of specific tasks, including the following: to select theoretical and linguistic material; to analyse and develop the general state of Shaanxi Northern folk songs and their translation; to identify the current state of research on the theory of linguistic picture of the world; to identify the relationship between linguistic realities, linguistic picture of the world and translation activities; to conduct inductive analysis of selected translations of Shaanxi Northern folk songs and analyse the manifestation of linguistic realities in them. Thus, the material for the study was songs from the north of Shaanxi Province. The subject of the study is to analyse the translations of these songs. The novelty of this work lies not only in the choice of original material, but also in the fact that by analysing the poetic and aesthetic characteristics of the folk songs of the north of Shaanxi province, at the same time we have tried to prove for the first time that the translator's ability to interpret this artistic phenomenon requires a broad background knowledge and poetic taste. We attribute the practical significance of our present study to its results, which may be useful in the dissemination of Chinese folk culture, particularly Chinese Shanbei songs among Russian-speaking peoples.

House cricket males reared at different perceived acoustic population densities differ in adult behaviour but not physiology

Abstract If environments stay relatively constant over an individual's lifetime, a juvenile that accurately perceives environmental conditions, like population density, may adjust adult traits to better match their environment, thereby increasing success. While previous studies have explored how adult exposure to population density affects physiological and behavioural plasticity, the influence of juvenile density experience on adult traits is less studied. Using the common house cricket, Acheta domesticus, we explored whether perceived acoustic population density during development affected adult physiology and behaviour. We simulated high‐ and low‐densities using live ambient male song. Upon maturation, we measured metabolic (resting respiration) rate, reproductive investment (testes and accessory gland masses), calling song characteristics and aggressive behaviours from pairwise contests between males from different densities. Male rearing density did not affect resting metabolic rates or reproductive organ masses. However, high‐density males had significantly faster, longer chirps, with more pulses—known to be preferred by females—and higher dominant frequency. Low‐density males won more aggressive contests and sang the aggressive song more. Initiation of aggressive behaviours or song and singing more aggressive song were the only other significant predictors of contest outcome. These results suggest that males may plastically adjust calling song characteristics and aggressive behaviour, but not physiology, based on perceived density during development. We hypothesize that alternative mating tactics—that is, territory guarding versus attractive song production—may underlie these observed patterns. Overall, our study highlights the significant influence of early‐life biotic environments on adult behavioural decisions to enhance success in diverse environments.

Daily singing of adult songbirds functions to maintain song performance independently of auditory feedback and age

Many songbirds learn to produce songs through vocal practice in early life and continue to sing daily throughout their lifetime. While it is well-known that adult songbirds sing as part of their mating rituals, the functions of singing behavior outside of reproductive contexts remain unclear. Here, we investigated this issue in adult male zebra finches by suppressing their daily singing for two weeks and examining the effects on song performance. We found that singing suppression decreased the pitch, amplitude, and duration of songs, and that those song features substantially recovered through subsequent free singing. These reversible song changes were not dependent on auditory feedback or the age of the birds, contrasting with the adult song plasticity that has been reported previously. These results demonstrate that adult song structure is not stable without daily singing, and suggest that adult songbirds maintain song performance by preventing song changes through physical act of daily singing throughout their life. Such daily singing likely functions as vocal training to maintain the song production system in optimal conditions for song performance in reproductive contexts, similar to how human singers and athletes practice daily to maintain their performance.

Comparative Analysis of Folk Song Styles in The Huizhou Region

The folk songs of the Huizhou region in Guangdong Province, China, are richly diverse and embody the area's profound cultural heritage. This study examines three distinct regional folk songs: the Huiyang Jiege, Ruhu Fishing Song, and Huidong Fishermen's Song, aiming to delineate their musical styles and cultural expressions and how they mirror the local culture. Utilizing both questionnaire surveys and in-depth interviews, this research engages with 326 residents and 16 cultural experts from various counties within Huizhou City. The study methodically evaluates the artistic features of these folk songs—including melody, theme, and lyrics—and investigates their transmission in contemporary times. The findings reveal that while these songs stem from a common cultural background, they exhibit distinct regional traits in their expression and social roles. For instance, the Huiyang Jiege is noted for its simple structure, whereas the Ruhu Fishing Song and Huidong Fishermen's Songs focus more on emotional expression and social interaction. The study advocates for enhanced local government support and collaborative research initiatives with universities. Additionally, it suggests leveraging modern media technologies to promote and preserve these folk songs as vital cultural assets. By thoroughly analyzing these locally distinctive folk songs, this research contributes to the academic field of ethnomusicology and offers valuable insights into the preservation and perpetuation of regional culture.

Enhancing Music Genre Classification through Multi-Algorithm Analysis and User-Friendly Visualization

The aim of this study is to teach an algorithm how to recognize different types of music. Users will submit songs for analysis. Since the algorithm hasn't heard these songs before, it needs to figure out what makes each song unique. It does this by breaking down the songs into different parts and studying things like rhythm, melody, and tone via supervised learning because the program learns from examples that are already labelled. One important thing to consider when classifying music is its genre, which can be quite complex. To ensure accuracy, we use five different algorithms, each working independently, to analyze the songs. This helps us get a more complete understanding of each song's characteristics. Therefore, our goal is to correctly identify the genre of each submitted song. Once the analysis is done, the results are presented using a graphing tool, making it easy for users to understand and provide feedback.

Music as a countermeasure to fatigue: A driving simulator study

Listening to music while driving is a commonly adopted fatigue-coping strategy, yet its effectiveness has been explored in only a limited number of studies. Here, we aim to evaluate its impact on passive task-related driving fatigue, as measured by a set of both objective and subjective indicators.A driving simulator experiment was conducted involving 60 participants, who completed a 50-minute driving task on a monotonous highway scenario. The participants were divided into a control group, which did not listen to any music, and an experimental group, which drove for 20 min without music and then listened to a self-selected music playlist played at the preferred intensity for the remaining 30 min.Results show that music had a positive acute effect on objective measurements of driving fatigue. However, this effect was transient (15–25 min duration), and more prominently observed in subjective measures of fatigue. An exploratory analysis of song features suggests that higher intensity, higher tempo, more danceable, and less instrumental music tend to be more effective. These findings indicate that listening to music can serve as a viable short-term countermeasure to driving fatigue.

Body size shapes song in honeyeaters.

Birdsongs are among the most distinctive animal signals. Their evolution is thought to be shaped simultaneously by habitat structure and by the constraints of morphology. Habitat structure affects song transmission and detectability, thus influencing song (the acoustic adaptation hypothesis), while body size and beak size and shape necessarily constrain song characteristics (the morphological constraint hypothesis). Yet, support for the acoustic adaptation and morphological constraint hypotheses remains equivocal, and their simultaneous examination is infrequent. Using a phenotypically diverse Australasian bird clade, the honeyeaters (Aves: Meliphagidae), we compile a dataset consisting of song, environmental, and morphological variables for 163 species and jointly examine predictions of these two hypotheses. Overall, we find that body size constrains song frequency and pace in honeyeaters. Although habitat type and environmental temperature influence aspects of song, that influence is indirect, likely via effects of environmental variation on body size, with some evidence that elevation constrains the evolution of song peak frequency. Our results demonstrate that morphology has an overwhelming influence on birdsong, in support of the morphological constraint hypothesis, with the environment playing a secondary role generally via body size rather than habitat structure. These results suggest that changing body size (a consequence of both global effects such as climate change and local effects such as habitat transformation) will substantially influence the nature of birdsong.

SDFIE-NET – A self-learning dual-feature fusion information capture expression method for birdsong recognition

Bird recognition is important for the monitoring of bird populations and the protection of ecosystems. Identifying birds through image forms can be difficult due to the complexity of natural environments. Song-based bird recognition allows for bird identification with only a small amount of background noise introduced, however, efficiently recognizing bird songs remains a challenging task. Based on this problem, this paper proposed a self-learning dual-feature fusion information capture expression method (SDFIE-NET) for recognizing birdsong. Firstly, using the Mel filter excerpt the low-frequency characteristics of the bird song. Since fixed-parameter filters are incapable of achieving different feature extraction effects based on different birdsong. In this paper, we incorporate a fully learnable audio classification front-end Leaf architecture for the extraction of bird song feature information, which can self-learn different extraction parameters for the birdsong. Effectively combining the high-frequency feature information and low-frequency differences acquired by the two approaches corresponds to the declared dual-feature fusion module (SCDFF), reducing information redundancy and improving characterization capability. Secondly, the backbone network utilizes SDFIE-NET, which is composed of the Fused-MBConv module and modified CA-MBConv module. The Criss-Cross Attention module is added after each layer composed of Fused-MBConv modules. This improves the speed and accuracy of effective information transfer between internal modules and increases the expressive power of the model at the pixel level. To enhance the anti-interference and generalization ability of the model, we constructed a self-made dataset (Bird_alldata) consisting of 30 kinds of birdsong. On this dataset, we performed a variety of experiments, and recognition accuracy reached 95.77 % and the F1-score reached 95.52 %. Generalization experiments were conducted on the environmental sound dataset Urbansound8K and the bird song dataset Birdsdata, and the model achieves recognition accuracies of 94.05 % and 94.10 % on the two datasets, with F1-scores of 94.21 % and 94.05 %, respectively.

Campur Kode dalam Lirik Lagu-Lagu Bagus Wirata: Kajian Sosiolinguistik

In recent years, the practice of code mixing in public communication in Bali has increased. Code mixing events can occur anytime and anywhere. One form of code mixing that has attracted attention is code mixing in pop song lyrics, especially Balinese pop songs. This is a concern in itself regarding the character of Balinese Pop songs, which were initially aimed at preserving Balinese art and culture, especially in terms of language, but have become something that seems to be forced solely for the sake of market demands. The formulation of the problem in this research is: 1) What is the form of code mixing in the lyrics of songs sung by Bagus Wirata 2) What factors encourage code mixing in the lyrics of songs sung by Bagus Wirata. The research approach used is an empirical method because the use of Balinese in the lyrics of Bagus Wirata's songs already exists naturally. The object of research in this research is the songs sung by singer Bagus Wirata. The data collection methods used were document study, observation and interviews.The research results are; 1. The form of code mixing in the lyrics of songs sung by Bagus Wirata is: The use of code mixing in the form of words is most often used in the lyrics of songs sung by Bagus Wirata with a total usage percentage of 63%. Code mixing in the form of clauses ranks second with a usage percentage of 19%. The remainder is code mixing in the form of phrases amounting to 13%, code mixing in the form of basters 3% and code mixing in the form of repeated words 2%. 2. Factors that encourage code mixing in the lyrics of songs sung by Bagus Wirata are; 1) language dominance, 2) language attitudes, 3) psycholinguistic motivation, 4) lack of equivalent words in Balinese, 5) commercial target market. 3. The impact of using code mixing on the Balinese language, namely; 1) destruction of the Balinese language system, 2) extinction of the Balinese language.