Oral biomechanical feature recognition method and system for vocal pronunciation resonance
Abstract
This paper discusses a vocal pronunciation resonance recognition method based on oral biomechanical features, aiming to collect the movement data inside the oral cavity through high-precision sensors, and combine support vector machines and convolutional neural networks to achieve precise recognition and optimization of pronunciation resonance features. First, by using high-precision sensors such as tongue position sensors and soft palate movement sensors, key biomechanical data such as tongue position, oral morphology and soft palate movement of singers during pronunciation are obtained in real-time. Then, feature extraction and analysis are performed to extract biomechanical features such as movement amplitude, frequency, and speed of oral organs, and a resonance feature recognition model is constructed using support vector machines and convolutional neural networks to recognize and optimize the resonance area during pronunciation. Finally, this paper designs and develops an automated recognition system that can provide real-time feedback on the singer’s pronunciation data, and provide personalized training suggestions based on the recognition results to optimize the pronunciation resonance effect. The experimental results show that the resonance recognition method based on biomechanical data can significantly improve the accuracy and personalization of pronunciation, and help improve the efficiency and scientificity of vocal training. The system has good stability, with a response time of less than 500 ms and a CPU (Central Processing Unit) usage rate of no more than 70%. This method provides effective technical support for the digitalization and personalized optimization of vocal pronunciation, and has high practical value and promotion potential.
References
1. Jeanneteau M, Hanna N, Almeida A, et al. Using visual feedback to tune the second vocal tract resonance for singing in the high soprano range. Logopedics Phoniatrics Vocology, 2022, 47(1): 25-34.
2. Maulana I, Lestiono R, Wiraatmaja T, et al. Arriving at pronunciation accuracy in singing English songs: Hijaiyah consonants as the mediation. Satwika: Kajian Ilmu Budaya Dan Perubahan Sosial, 2021, 5(2): 303-316.
3. Titze I. Training the Vocal Instrument. Journal of Singing, 2019, 76(1): 43-46.
4. Xie X. On the integration of national singing and bel canto in vocal music teaching in normal universities. Transactions on Comparative Education, 2021, 3(3): 18-22.
5. Jang K, You K B, Park H. A Study on Correcting Korean Pronunciation Error of Foreign Learners by Using Supporting Vector Machine Algorithm. International Journal of Advanced Culture Technology, 2020, 8(3): 316-324.
6. Graf S, Schwiebacher J, Richter L, et al. Adjustment of vocal tract shape via biofeedback: influence on vowels. Journal of Voice, 2020, 34(3): 335-345.
7. Li M, Khysru K, Shi H, et al. A 3D Geometry Model of Vocal Tract Based on Smart Internet of Things. Comput. Syst. Sci. Eng., 2023, 46(1): 783-798.
8. Jin L. Research on the construction of English exams for healthcare professionals in the health sector. Journal of Commercial Biotechnology, 2022, 27(5): 175-187.
9. Duan G, Zeng J, Ji H. THE IMPORTANCE OF PSYCHOLOGICAL ANALYSIS TO VOCAL MUSIC SINGING TEACHING. Psychiatria Danubina, 2021, 33(suppl 7): 315-317.
10. Xie X. On the Integration of Bel Canto and Popular Singing in Vocal Music. International Core Journal of Engineering, 2021, 7(3): 1-4.
11. Baolin Z, Yodwised C. Constructing the Children Chorus Guidebook for Teaching Student at Jinhua Primary School in Zhengzhou, Henan Province. Asia Pacific Journal of Religions and Cultures, 2024, 8(1): 63-77.
12. Yao Y. The Study of the Effects of Yunnan Yuxi Dialect on Received Pronunciation. Theory and Practice in Language Studies, 2020, 10(6): 664-671.
13. Zhou Q, Liu S, Dai C, et al. A study of the resonance peak characteristics of Mongolian long-key ode. Advances in Education, Humanities and Social Science Research, 2023, 6(1): 291-291.
14. Deng S, Phokha P, Chiangthong N. The Creation of Vocal Performance Course Case Study Guangxi Arts University. Sciences of Conservation and Archaeology, 2024, 36(4): 139-149.
15. Kelly R. Latin Pronunciations for Singers: A Comprehensive Guide to the Classical, Italian, German, English, French, and Franco-Flemish Pronunciations of Latin. The Choral Journal, 2019, 59(11): 88-89.
16. Pocan O. Vocal Composition in Creating the Commedia dell’Arte Characters. Studia Universitatis Babes-Bolyai-Dramatica, 2023, 68(1): 175-189.
17. Gong N. Discussion on the “Localization” Singing Technique Transformation of Opera in the Background of Chinese Culture. Review of Educational Theory, 2019, 2(1): 16-20.
18. Duan L. The application of modern virtual reality technology in the teaching of vocal music. Curriculum and Teaching Methodology, 2023, 6(19): 77-81.
19. Zhang Y. Research and application of spoken English evaluation system based on biological voiceprint feature recognition. International Journal of Wireless and Mobile Computing, 2022, 22(2): 194-203.
20. Wu P, Wang R, Lin H, et al. Automatic depression recognition by intelligent speech signal processing: A systematic survey. CAAI Transactions on Intelligence Technology, 2023, 8(3): 701-711.
21. Wan M. Designing an online vocal learning based on ZigBee-enabled wireless platform. Wireless Networks, 2024, 30(1): 179-192.
22. Gao S. The Construction Of Students' Aesthetic Ability In Opera Singing Teaching Based On Vocal Aesthetics. Educational Administration: Theory and Practice, 2024, 30(4): 1723-1728.
23. Chen W L, Ye Q, Zhang S C, et al. Aphasia rehabilitation based on mirror neuron theory: a randomized-block-design study of neuropsychology and functional magnetic resonance imaging. Neural regeneration research, 2019, 14(6): 1004-1012.
24. Bin F. The Application and Inheritance of Chinese Ancient Poetry and Art Songs in Vocal Teaching. Art and Performance Letters, 2024, 5(4): 1-6.
25. Făgărășan R C. The Diction in the Art of Singing in the English Language. Învăţământ, Cercetare, Creaţie, 2023, 9(1): 106-113.
26. Zixuan L. Research on the current situation of Chinese national vocal music education from the perspective of educational psychology. Frontiers in Art Research, 2021, 3(6): 48-58.
27. Chiaramonte R, Di Luciano C, Chiaramonte I, et al. Multi-disciplinary clinical protocol for the diagnosis of bulbar amyotrophic lateral sclerosis. Acta Otorrinolaringologica (English Edition), 2019, 70(1): 25-31.
28. Surahman A. An analysis of voice spectrum characteristics to the male voices recording using praat software. IJFL (International Journal of Forensic Linguistic), 2021, 2(2): 69-74.
29. Fagarașan R C. Pronunciation in the Art of Singing in English and French During the Middle Ages. Învăţământ, Cercetare, Creaţie, 2023, 9(1): 97-105.
30. Janaswamy R, Vasudev S K. Vocal Training and Practice Methods: A Glimpse on the South Indian Carnatic Music. International Journal of Humanities and Social Sciences, 2020, 14(12): 1281-1285.
31. Moran W. Discussion on the Characteristics and Skills of Tenor Singing in Different Musical Styles. Art and Performance Letters, 2024, 5(3): 97-102.
32. Chen S, Gan R. Analysis of the Acoustic Characteristics of the Stops in Northern Yi Dialects. Journal of Sociology and Ethnology, 2024, 6(3): 19-28.
33. Junjie L, Meesorn P. Overview of the Bel Canto and Development. Journal of Modern Learning Development, 2024, 9(8): 769-777.
34. Suhery D, Idami Z, Wati S. The Phonological Interference of Acehnese in Pronouncing Indonesian Language. Journal of Languages and Language Teaching, 2024, 12(1): 120-135.
35. Wu H X, Li Y, Ching B H H, et al. You are how you speak: The roles of vocal pitch and semantic cues in shaping social perceptions. Perception, 2023, 52(1): 40-55.
36. Duyen T M T. Exploring Phonetic Differences and Cross-Linguistic Influences: A Comparative Study of English and Mandarin Chinese Pronunciation Patterns. Open Journal of Applied Sciences, 2024, 14(7): 1807-1822.
37. Sun X. The Training Value of Handel’s Vocal Works in Vocal Pedagogy. Research and Advances in Education, 2023, 2(3): 19-22.
38. Hasanah N, Rahmadhani P R, Lubis Y. Inconsistency of Some Consonants in English. Jurnal Pendidikan Rafflesia, 2023, 1(2): 31-34.
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