Piano playing teaching system based on artificial intelligence – design and research

Liu, Meichen; Huang, Jieru

doi:10.3233/jifs-189389

Cited by 49 publications

(35 citation statements)

References 10 publications

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“…During this period, the performer's ability to correctly understand other people's emotions is cultivated, and with the help of music, the ability to perceive other people's emotions is improved. In a word, learning piano plays a role in promoting all-round development, improving people's comprehensive ability level, and has important signi cance and e ect on ability development and training [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Piano Intelligent Teaching Evaluation with IoT and Multimedia Technology

Wang

Bai

2022

Mobile Information Systems

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With deepening of the economic development process, the overall spiritual and cultural needs of the people have increased, and quality education has received more and more attention. Piano education is an important part of quality education. Nowadays, piano education has also been able to move forward continuously. As the king of musical instruments, the piano is widely used in music learning. Learning the piano can exercise willpower, develop intelligence, and cultivate sentiment. With development of computer software as well as hardware, Internet of Things technology and multimedia technology provide the material basis and preconditions for intelligent piano teaching. Therefore, how to evaluate the impact of the IoT and multimedia technology on intelligent teaching of piano has become a very important topic. Based on this, this work combines BP network with artificial fish swarm algorithm (AFS) and proposes network model (IAFS-BP) for evaluating the quality of piano intelligent teaching in the context of Internet of Things and multimedia. The specific contents of this work are as follows: (1) Aiming at the shortcomings of AFS, an IAFS with mutation operator, dynamic vision, and step size is proposed. (2) In view of shortcomings for BP network, IAFS is used in BP network. By using the IAFS algorithm in the training of the weights as well as thresholds, the training speed and training accuracy of the network are improved. (3) This work has carried out a comprehensive and systematic experiment to verify effectiveness and feasibility of IAFS-BP applied to quality assessment of piano intelligent teaching in the context of the IoT and multimedia.

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Section: Introductionmentioning

confidence: 99%

Piano Intelligent Teaching Evaluation with IoT and Multimedia Technology

Wang

Bai

2022

Mobile Information Systems

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“…It can be realized through display and control. Students can complete music exercises through mobile phones [ 19 ]. In order to make the exercises more effective, the system can make sounds through mobile phones, including accompaniment questions and demonstrations of famous works.…”

Section: Design and Test Of Music Online Education System Based On Mo...mentioning

confidence: 99%

Design of Online Music Education System Based on Artificial Intelligence and Multiuser Detection Algorithm

Hua

2022

Computational Intelligence and Neuroscience

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With the development of information technology, online music education has become a mainstream education method. Especially after the outbreak of COVID-19, music teachers have to teach through online. Therefore, an online music education system that can improve the quality of teaching is particularly important. Multiuser detection algorithms and artificial intelligence have important applications in many fields, and the field of music online education is no exception. This paper takes the music teaching of the music distance teaching unit as the goal and conducts sufficient research on the educational subjects such as teachers, students, and administrators. And with the help of the SCMA system multiuser detection algorithm and artificial intelligence technology, the system analysis and design method is used to analyze and design the music teaching function system. The system module involves basic information management, student music assignments, online courses, and other levels, providing an excellent educational system design example for music online education. The conclusion analysis shows that the music online education system based on SCMA system multiuser detection algorithm and artificial intelligence designed in this paper can significantly improve the audience’s music learning efficiency and has obvious benefits to the student group.

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“…The authors utilized this algorithm to recompile the multi-voice model to construct a multi-voice recognition system, which offered inspiration for the system model of intelligent network piano teaching. Liu and Huang (2021) proposed an intelligent piano teaching system based on a neural network. The system realized the overall function of piano playing, including MIDI signal extraction, neural network model construction, playing interface, fiveline animation, and evaluation interface.…”

Section: Related Workmentioning

confidence: 99%

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

2022

Front. Psychol.

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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.

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Piano playing teaching system based on artificial intelligence – design and research

Cited by 49 publications

References 10 publications

Piano Intelligent Teaching Evaluation with IoT and Multimedia Technology

Piano Intelligent Teaching Evaluation with IoT and Multimedia Technology

Design of Online Music Education System Based on Artificial Intelligence and Multiuser Detection Algorithm

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

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