Enhancing Vocal Performance Through Computer-Assisted Training

Збережено в:
Бібліографічні деталі
Опубліковано в::International Journal of Web-Based Learning and Teaching Technologies vol. 20, no. 1 (2025), p. 1-18
Автор: Chen, Liping
Опубліковано:
IGI Global
Предмети:
Онлайн доступ:Citation/Abstract
Full Text - PDF
Теги: Додати тег
Немає тегів, Будьте першим, хто поставить тег для цього запису!

MARC

LEADER 00000nab a2200000uu 4500
001 3222668941
003 UK-CbPIL
022 |a 1548-1093 
022 |a 1548-1107 
024 7 |a 10.4018/IJWLTT.381310  |2 doi 
035 |a 3222668941 
045 2 |b d20250101  |b d20251231 
100 1 |a Chen, Liping  |u Xiamen Huaxia University, China 
245 1 |a Enhancing Vocal Performance Through Computer-Assisted Training 
260 |b IGI Global  |c 2025 
513 |a Journal Article 
520 3 |a In the evolving landscape of vocal pedagogy, the integration of computer-assisted technologies represents a transformative shift from traditional master-apprentice models. This study investigates the efficacy of computer-assisted vocal training methods compared to conventional approaches, focusing on improvements in pitch accuracy, vocal range expansion, and emotional expression among novice vocalists. Utilizing a mixed-methods approach, including digital signal processing, machine learning, and virtual reality, the authors conducted a 12-week experiment involving 60 participants randomly divided into two groups. Results indicate that computer-assisted training offers nearly double the improvement in pitch accuracy and vocal range expansion over traditional methods, with more pronounced enhancements in emotional expression skills. These findings contribute significantly to developing standardized, personalized, and scientifically-grounded vocal training methodologies, demonstrating a more efficient pathway for enhancing vocal performance. 
653 |a Teaching 
653 |a Computer assisted instruction--CAI 
653 |a Technological change 
653 |a Collaboration 
653 |a Wavelet transforms 
653 |a Machine learning 
653 |a Signal processing 
653 |a Virtual reality 
653 |a Efficacy 
653 |a Emotions 
653 |a Facial expressions 
653 |a Singers 
653 |a Computers 
653 |a Digital signal processing 
653 |a Fourier transforms 
653 |a Algorithms 
653 |a Apprentices 
653 |a Education 
653 |a Accuracy 
653 |a Pedagogy 
653 |a Training 
653 |a Interdisciplinary aspects 
653 |a Self expression 
653 |a Feedback 
653 |a Longitudinal studies 
653 |a Voice training 
653 |a Experiential learning 
653 |a Customization 
653 |a Vocal range 
653 |a Acoustics 
653 |a Computer Simulation 
653 |a Literature Reviews 
653 |a Intergroup Education 
653 |a Innovation 
653 |a Short Term Memory 
653 |a Artificial Intelligence 
653 |a Instructional Effectiveness 
653 |a Learning Modules 
653 |a Cross Cultural Training 
653 |a Audio Equipment 
653 |a Information Retrieval 
653 |a Influence of Technology 
653 |a Kinesthetic Perception 
653 |a Periodicals 
653 |a Art Expression 
653 |a Time 
653 |a Computer Assisted Instruction 
653 |a Skill Development 
653 |a Training Methods 
653 |a Interdisciplinary Approach 
773 0 |t International Journal of Web-Based Learning and Teaching Technologies  |g vol. 20, no. 1 (2025), p. 1-18 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3222668941/abstract/embedded/H09TXR3UUZB2ISDL?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3222668941/fulltextPDF/embedded/H09TXR3UUZB2ISDL?source=fedsrch