Piano Performance Research Articles

Illuminating Music: Impact of Color Hue for Background Lighting on Emotional Arousal in Piano Performance Videos.

This study sought to determine if hues overlayed on a video recording of a piano performance would systematically influence perception of its emotional arousal level. The hues were artificially added to a series of four short video excerpts of different performances using video editing software. Over two experiments 106 participants were sorted into 4 conditions, with each viewing different combinations of musical excerpts (two excerpts with nominally high arousal and two excerpts with nominally low arousal) and hue (red or blue) combinations. Participants rated the emotional arousal depicted by each excerpt. Results indicated that the overall arousal ratings were consistent with the nominal arousal of the selected excerpts. However, hues added to video produced no significant effect on arousal ratings, contrary to predictions. This could be due to the domination of the combined effects of other channels of information (e.g., the music and player movement) over the emotional effects of the hypothesized influence of hue on perceived performance (red expected to enhance and blue to reduce arousal of the performance). To our knowledge this is the first study to investigate the impact of these hues upon perceived arousal of music performance, and has implications for musical performers and stage lighting. Further research that investigates reactions during live performance and manipulation of a wider range of lighting hues, saturation and brightness levels, and editing techniques, is recommended to further scrutinize the veracity of the findings.

Research on Piano Performance Optimization Based on Big Data and BP Neural Network Technology.

At present, there are many chess styles in piano education, but there is a lack of comprehensive, scientific, and guiding teaching mode. It highlights many educational problems and cannot meet the development requirements of piano education at this stage. However, the piano scoring system can partially replace teachers' guidance to piano players. This paper extracts the signal characteristics of playing music, establishes the piano performance scoring model using Big Data and BP neural network technology, and selects famous works to test the effect of the scoring system. The results show that the model can test whether the piano works fairly. It can effectively evaluate the player's performance level and accurately score each piece of music. This not only provides a reference for the player to improve the music level but also provides a new idea for the research results and the application of new technology in music teaching. This paper puts forward reasonable solutions to the problems existing in piano education at the present stage, which is helpful to cultivate high-quality piano talents. Experiments show that the application of Big Data technology and BP neural network to optimize the piano performance scoring system is effective and can score piano music accurately. This paper studies the performance scoring system and gets the model after training, which can replace music teachers and alleviate the shortage of music teachers in the market.

Touching through Music, Touching through Words

This article investigates the versatile embodiment of touch in the sensory-aesthetic construction of piano performance. The sensorial interactions enmeshed in piano playing distribute a peculiar interaction between touch and sound, which can be comprehended as two kinds of pianistic touch – the physical touch and the affective touch. In the synthesis, or symbiosis, of these two kinds of touch, piano performance epitomizes a sensory-aesthetic continuum to transmit its force beyond perceptible spatial-temporal boundaries. This article argues that the tactile-sonic relationship in piano playing manifests the performative power of music to formulate new modes of feeling and understanding. This argument is explored in three stages. The first stage utilises two treatises, Steven Connor's ‘Edison's teeth’ (2001) and Simon Waters’ ‘Touching at a distance’ (2013), to explicate how touch enables the production of musical sound and how music can be received as tactually oriented sensations. The second stage introduces the piano as an exemplary instrument of touch in the contexts of scientific studies and relevant cultural history. The third stage uses two novelistic texts as heuristics to explore how pianistic touch is enacted performatively to engage with the aural, visual, somatic and visceral sensations. Both Thomas Mann's ‘Tristan’ (2009 [1903]) and Forster's A Room with a View (2012 [1908]) testify to how fictional presentations of piano playing can provide fertile loam to reappraising pianistic touch beyond the ordinary musical context. Overall, as performed in a range of pianistic settings, the multivariant senses of touch provide productive perspectives for re-constructing what prior categories of senses and sensations could not consider. This article will thus be conducive to a quest for new forms of creativity underlying the performance and performativity of pianistic touch.

Children's feelings about piano performances across a year of study.

Solo performance is a common experience for children learning to play an instrument, yet the research literature on these experiences is limited, with a focus on older children and adolescents. The purpose of this study was to examine younger children’s feelings about performance over the course of a year of study. Forty-one children were interviewed about their piano lessons and performance experiences at the end of two consecutive semesters of study. They also responded to a pictorial scale on their feelings about performance at each interview and again at two piano recitals. Results indicate that children are remarkably consistent in their feelings about performing in piano recitals, with few significant changes over time and context. Correlation analyses indicate changes in the relationships between feelings about performance and certain study variables over time—in particular age, liking of lessons, liking of performing, practice time, and perception of being good at piano. In the fall term, gender and age are significant predictors of feelings about performance, with younger children and boys feeling most positive. In the spring, the findings shift and the only significant predictor is children’s liking of piano lessons. Implications and directions for further research are discussed.

The Piano-Assisted Teaching System Based on an Artificial Intelligent Wireless Network

In the recent technological era, we can note a tremendous development in the information technology sector, which has made all other sectors work to face a revolution and profit. In comparison with other organizations, educational departments have shown the best utilization of technology in their teaching and learning process. Teaching and learning (TaL) music and musical instruments are very challenging for teachers and students of remote areas. In this research work, TaL of piano playing is considered for the study by taking the MIDI and Audio Edited for Synchronous TRacks and Organization (MAESTRO) dataset. This dataset has virtual recorded piano performances with a label for notes and audio waveforms. The multiple signal classification (MSC) algorithm with the artificial intelligence (AI) is implemented on the dataset to train the students with artificial intelligence’s support. This MSC algorithm is executed on wireless networks (WN) to classify the signal data after recording and updating the dataset. With the help of the MSC algorithm with WN, the selection of teachers becomes easier for the student. This proposed work shows effective results for the TaL performance.

Analysis of Piano Performance Characteristics by Deep Learning and Artificial Intelligence and Its Application in Piano Teaching.

Deep learning (DL) and artificial intelligence (AI) are jointly applied to concrete piano teaching for children to comprehensively promote modern piano teaching and improve the overall teaching quality. First, the teaching environment and the functions of the intelligent piano are expounded. Then, a piano note onset detection method is proposed based on the convolution neural network (CNN). The network can analyze the time-frequency of the input piano music signal by transforming the original time-domain waveform of the piano music signal into the frequency distribution varying with time. Besides, it can detect the note onset at a stable state after 8 × 104 iterations. Moreover, an intelligent piano teaching method is designed to teach Jingle Bells for 40 preschool children aged 4–6 years. Finally, a questionnaire survey is performed to investigate the teaching situation, including the learning interest and learning effect of children and learning feedback from parents. The results show that 80% of children like smart music scores, 82% of children like intelligent piano lessons with games, and 84% of children can learn actively in the intelligent piano class. Besides, 85% of parents believe that their children are more interested in learning piano. In general, the intelligent piano teaching method effectively combines DL with AI to realize the overall optimization of piano performance. It is widely favored by preschool children and their parents and plays an important role in improving the interest of preschool children in piano learning.

Piano Music Teaching under the Background of Artificial Intelligence

The work is aimed at solving the problems of easy trapping into local extremes and slow convergence speed of the traditional music teaching evaluation system on Backpropagation Neural Network (BPNN). The traditional note recognition methods are susceptible to high noise complexity. Firstly, the Levenberg Marquardt (LM) algorithm is used to optimize the BPNN; secondly, an improved endpoint detection algorithm is proposed by short-term energy difference, which can accurately identify the time value of each note in the piano playing audio. By the traditional frequency domain analysis method, a radical frequency extraction algorithm is proposed by the improved standard harmonic method, which can accurately identify the note’s pitch. Finally, a piano performance evaluation model by BPNN is implemented, and the model is implemented by the Musical Instrument Digital Interface (MIDI) system. This evaluation model can be used to correct the errors of students’ performances in the piano music teaching process and to perform overall evaluation, rhythm evaluation, and expressive evaluation. Teachers and students play minuet to collect experimental samples to train BPNN and test the performance of the evaluation model. The practical result shows that (1) after 3000 times of training, the neural network error is less than 0.01, and the network converges; (2) the evaluation results of the piano performance evaluation model designed are basically in line with the actual level of the performer and have specific feasibility; and (3) the optimized BPNN is used to correct errors during performances with an accuracy rate of 94.3%, which is 5.25% higher than the traditional method. The error correction accuracy rate for pitch is 92.9%, which is 5.21% higher than the traditional method. The optimized BPNN has significantly improved the error correction accuracy of the notes and pitches played by the player. The model can effectively help piano beginners correct errors and improve the accuracy and efficiency of the practice. The purpose of this study is to alleviate the scarcity of piano teachers, reduce the work intensity of piano teachers, realize automatic error correction and objective evaluation of playing, and provide necessary technical support for improving the efficiency of piano music teaching.

Toward Piano Teaching Evaluation Based on Neural Network

With the rise of piano teaching in recent years, many people participated in the team of learning steel playing. However, expensive piano teaching fees and its unique one-to-one teaching model have caused piano education resources to be very short, so learning piano performance has become a very extravagant event. The factors affecting music performance are varying, and there are many types of their evaluation such as rhythm, expressiveness, music, and style grasp. The computer is used to simulate this evaluation process to essentially identify the mathematical relationship between factors affecting music performance and evaluation indicators. The use of computer multimedia software for piano teaching has become a feasible way to alleviate the contradiction. This paper discusses the implementation method of piano teaching software, the issues of computer piano teaching, the computer teaching as one-way knowledge, and the lack of interaction. The neural network (NN) model is used to evaluate the piano performance and simulate teachers to guide students through their exercise. The performance of the proposed system is tested for the piano music of “Ode to Joy,” which is different from the collection of NN training samples, and is delivered ten times by another piano teacher, student A (piano level 6), and student B (piano level 5).

The Museum of Musical Instruments as a Means of Optimizing the Professional Training of the Future Bachelor of Musical Arts

The article presents the history of organization if the museum of musical instruments. The idea of its exposition was formed by the rare keyboard instruments, collected within many years of expert activity. The experience of internship in the European museums and universities had influenced the vision of the evaluation and determination of cultural values among musical instruments. The preparation and teaching of the disciplines “The Expertise of Musical Instruments”, “Clavier and Piano Performance”, “The History of Harpsichord and Piano Art”, “The History of Styles and Performing Interpretation”, 11 articles in research journals, devoted to historical instruments, together with more than 50 years of performing activity on many stages of our country and Europe have demonstrated that the instrument has great importance in the process of getting of the high level of professionalism and the reception of musical material by the audience.

Discussion on the Teaching Mode of Piano Performance from the Perspective of Aesthetics

After incorporating "piano" as an important content of general education in colleges and universities into the syllabus, people began to focus on how to build a piano teaching system suitable for our country, and how to innovate a series of issues such as how to innovate piano creation with Chinese national spirit and style. Among them, the piano performance is unique in style, and its teaching and aesthetic aspects are also different from many music. This has caused a lot of trouble to the establishment of the goals, contents and methods of piano teaching in professional music colleges, resulting in a practical paradox that is difficult to solve. Find an ingenious balance between the spirit of the original work and the use of creative thinking, seek a proper coordination between historical style and era style, and achieve a perfect unity between performance technology and artistic expression. The exploration method combining aesthetics and piano teaching in this paper further reveals the compatibility and promotion of various disciplines, which can play an effective reference role in piano teaching.

Postural Variability in Piano Performance

Variability is inevitable in human movement and posture, including piano performance, although little research has been conducted in this area. The purpose of this study was to determine if, when comparing individuals to themselves, pianists demonstrate consistent postural angles within a task across multiple measurements and to ascertain if, between various tasks, there are discernible task-related postural patterns. Fifteen pianists participated in this study. Each pianist returned for a total of three measurement sessions. The tasks they were required to perform at each session were quiet sitting, raising their hands on and off the keyboard, playing an ascending and descending scale, sight reading, and playing a piece in three expressive conditions (i.e., deadpan, projected, exaggerated). The following postural angles were calculated based on motion capture data collected during the performance of these tasks: craniovertebral angle, head tilt, head-neck-trunk angle, trunk angle, thoracic angle, thoracolumbar angle, and lumbar angle. The within-person variability ratio across the three measurements was calculated for each angle and across all tasks. Task-related patterns in angles were examined by comparing the same postural angle across different tasks. Results showed that there is a considerable amount of within-person variability, but not enough to be inconsistent over time. Task-related patterns indicate that reading a musical score or playing at the extreme ends of the keyboard tend to involve leaning closer to the instrument. Implications for future studies, intervention studies in particular, include taking more than a single baseline measurement to provide a more accurate picture of an individual pianist's typical posture.

Research on the Flipped Classroom of Online Open Courses Driving Piano Foundation Courses in Colleges and Universities: A Case Study of Piano MOOC

In recent years, with the rapid development of Internet and new media technology, the undergraduate teaching mode has shown new characteristics such as networking, interactivity, generative and fragmentation. Due to the continuous heating up of "piano fever" in China in recent years, the expansion of the music departments of major music colleges and normal colleges, and the strong demand for piano performance and teaching staff in the society, the traditional one-to-one piano teaching mode can no longer meet the needs of piano teaching in various music colleges, and the basic piano courses came into being. At present, most of the piano courses in colleges are large class teaching, the form of online "MOOC" in the teaching of piano basic courses can not only promote students' independent learning, greatly alleviate the shortage of teachers, but also make an important supplement and expansion of traditional classroom learning.

About Some Universals of Pedagogical Thought in the Field of Piano Performance

About Some Universals of Pedagogical Thought in the Field of Piano Performance

Effects of piano performance with KAATSU twice daily for 3 weeks on neuromuscular mechanisms: a case study

Effects of piano performance with KAATSU twice daily for 3 weeks on neuromuscular mechanisms: a case study

Discussion on countermeasures of improving students' expressive force in piano performance teaching

With the continuous progress of China's social economy and the continuous development of science and technology, education is also prosperous and developed. As Piano belongs to art courses, so it requires students to master sufficient theoretical knowledge，professional application，practice ability and have high enough enthusiasm to devote themselves to learning and maximize their own performance. However, in the actual teaching process of colleges and universities, students are taught how to play while ignoring the cultivation and improvement of their own expressive force. In this paper, the author of piano teaching and music performance as the breakthrough point, actively explore how to improve students' music performance in college teaching.

Ternopil branch of the Musical Institute named after Mykola Lysenko as a cultural and educational center of Ternopil (1st half of XX century)

The purpose of the article is to analyze the historical and cultural background and the main aspects of the formation of professional piano performance in Ternopil in the late nineteenth - first half of the twentieth century on the example of VMIL branch activity. Methodology. The methodological basis of the publication is historical-stylistic and comparative approaches, methods of historical-cultural discourse (according to V. Cherkasov). The formation of professional piano performance is considered in terms of musicological and stylistic approaches in broader cultural, educational, and musical-pedagogical contexts. The problem of studying the regionalism of music and performance centers and schools as a dynamic historical and cultural phenomenon is actualized. A thorough study of the history of regional piano educational centers and performing schools has been the subject of a number of musicological studies. In particular, the works of N. Kashkadamova, T. Starukh, L. Mazepa, and others are dedicated to the piano art of Lviv, its artistic education, and cultural institutions. Scientific Novelty. Based on the study of scientific and archival sources, we can see that the educational and pedagogical traditions of the Higher Music Institute named after M. Lysenko as the first Ukrainian professional center and its branches in Eastern Galicia have continued in the activities of pianists, teachers, and performers in Ukraine and abroad, mainly Western Of Ukraine. Attention is focused on the opening and initial stage of the branch of the Lysenko Higher Music Institute (VMIL) in Ternopil, in particular, on the activities of piano teachers. Based on historical, comparative, and individual approaches, the role of individual performers, composers, and teachers as the founders of piano performance in the region is highlighted. Thus, the novelty of the article is to trace the initial stage of the formation of piano performance in Ternopil in the late nineteenth - first third of the twentieth century. as a process of transition from the amateur period to academic performance and professional music education. Conclusions are made about the decisive role of the branch of the Higher Music Institute named after M. Lysenko (VMIL) in Ternopil and its founders, in particular, Iryna Krykh (Lyubchakova) and Yuri Krykh, in the development of music education and performance in the region. Keywords: musical culture of Western Ukraine, end of XIX – first half of XX century, piano performance, Higher Music Institute M. Lysenko (VMIL), pianists, performers and lecturers of Ternopil.

Multimedia Recognition of Piano Music Based on the Hidden Markov Model

Piano performance is an art with rich artistic elements and unpredictable performance skills. It is an important carrier for playing beautiful piano sounds. The generation of musical tension and expression of piano performance is a vivid display of piano performance skills. In piano performance, we should pay attention to the cultivation and flexible application of performance skills. In order to ensure the richness and artistry of piano performance, it is fully based on the artistic characteristics of piano performance. Through in-depth analysis of the principle of the hidden Markov model, it is applied to the multimedia recognition process of piano playing music. In the process of obtaining the template, the fundamental frequency of the piano playing music differs greatly, and the piano playing music appears during the performance process. For the problem of low recognition rate, this paper proposes a multimedia recognition method for piano music. Finally, the analysis of experimental results shows that the method proposed in this paper has a 16% higher recognition rate than the traditional method, and it has a certain value in the multimedia recognition of piano music.

Reproduction performance means of the piano work texture program (on the example of the cycle “Shevchenko’s Suite” by B. Liatoshynskyi)

The article is devoted to revealing the peculiarities of the texture program performance reproduction of a musical work. Based on the consideration of the textural program as a sequence of changes in the musical performance during the process of developing the form of the work, the performer-pianist must build the appropriate means of performance: artistic and technical ones. An important role here belongs to the author and the editorial remarks, the content of which, however, is quite conditional and requires individual performance correction.
 The topicality of the chosen topic lies in the need for in-depth consideration of the problems of musical texture and its attributes in the piano-performance specification.
 The purpose of the research is to identify the performance component of the piano work textural program, to propose an algorithm for its analysis on a specific example of B. Liatoshynskyi’s cycle.
 The methodology: the article uses a set of general scientific and special musicological approaches for developing the content of the stated topic. Among them are the following methods: systematic and structural method, it is aimed at revealing the essence of the phenomenon of the musical work textured program; a deductive method, it determines the course of research in the direction from a general part (textural program of a musical work) to a special (specificity of textural performance during a piano work) and a specific one (textural programs of plays of the cycle by B. Liatoshynskyi); genre and stylistic types of analysis from the point of view of reproduction of these phenomena in textural programs; texture analysis as a kind of musicological analysis; performance analysis, which is aimed at identifying the features of the textural attributes of the work under consideration.
 The results of the study show that the process of a piano work performance in the direction of its full interpretation is inseparable from analytical observations on the texture program and its attributes. The set of analytical and performance-technical procedures has as its ultimate goal the act of performing a piano work, in which the composer’s intentions are reproduced by means of the individual style of the pianist.
 The novelty of this study is the extrapolation of ideas about the piano work textural program on the interpretive activities of the performer. Embodying own understanding of the textural process and its attributes in the interpretation, the performer demonstrates personal version of the work sound image, revealing the means of the drama and composition art features.
 The practical significance of the study lies in the possibility of using its provisions and conclusions in the courses “Musical Interpretation”, “Analysis of Musical Works”, “History of Piano Performance”, as well as in classes specializing in “piano” for bachelors and masters of the higher educational institutions of art and culture of Ukraine.
 Conclusions. Thus, the concept application of the piano work “texture program” in relation to the activities of the performer-interpreter raises a number of issues related to the means of the performance center: dynamics, articulation, agogics, in their vision by the musical composer and directly the performer. In this context, the identification and implementation of the piano work textured program gives the key to the disclosure of its ideological and artistic content, a clear understanding of the drama and form features, implemented in the act of performance.

Automatic Evaluation of Piano Performances for STEAM Education

Music plays an important part in the lives of people from an early age. Many parents invest in music education of various types for their children as arts and music are of economic importance. This leads to a new trend that the STEAM education system draws more and more attention from the STEM education system that has been developed over several years. For example, parents let their children listen to music since they were in the womb and invest their money in studying music at an early age, especially for playing and learning musical instruments. As far as education is concerned, assessment for music performances should be standardized, not based on the individual teacher’s standard. Thus, in this study, automatic assessment methods for piano performances were developed. Two types of piano articulation were taken into account, namely “Legato” with vibration notes using sustain pedals and “Staccato” with detached notes without the use of sustain pedals. For each type, piano sounds were analyzed and classified into “Good”, “Normal”, and “Bad” categories. The study investigated four approaches for this task: Support Vector Machine (SVM), Naive Bayes (NB), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM). The experiments were conducted using 4680 test samples, including isolated scale notes and kids’ songs, produced by 13 performers. The results show that the CNN approach is superior to the other approaches, with a classification accuracy of more than eighty percent.

A comparative study of piano performance programs at university-level institutions in China and the United States: From current faculty members’ and students’ perspectives

This study investigated the perceptions of piano performance programs in higher education from current collegiate students and faculty members’ perspectives in China and the United States. Participants were from representative university-level institutions in the U.S. ( n = 41) and China ( n = 130). They were sent a questionnaire concerning (a) the factors that motivate students to pursue a piano performance degree, (b) the most important educational practices in their programs, (c) the most challenging tasks the students encounter, (d) students’ career goal, and (e) faculty members’ suggestions for prospective students and opinions on improving the piano performance programs. A summary of students and faculty members’ perceptions were outlined and the comparison between the two countries were explored. It is encouraging that not only students gave careful attention toward the applied lessons and performance opportunities in their studies, but also that a large percentage of the students believed they received excellent advice regarding practice strategies and artistry in their applied lessons in both countries. Most of the faculty participants in both countries expressed positive attitudes regarding the piano performance programs in their universities. By providing statistically significant data, this study provides a comprehensive vision for institutions to continue establishing piano programs.