請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/90777完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 李尉彰 | zh_TW |
| dc.contributor.advisor | Wei-Chang Li | en |
| dc.contributor.author | 許哲諭 | zh_TW |
| dc.contributor.author | Che-Yu Hsu | en |
| dc.date.accessioned | 2023-10-03T17:34:22Z | - |
| dc.date.available | 2023-11-10 | - |
| dc.date.copyright | 2023-10-03 | - |
| dc.date.issued | 2023 | - |
| dc.date.submitted | 2023-08-11 | - |
| dc.identifier.citation | [1] Wikipedia. "Throat microphone." https://en.wikipedia.org/wiki/Throat_microphone (accessed.
[2] OTTO. OTTO Throat Microphone [Online] Available: https://www.otto-comm.com/products/throatmicrophones/throatmicrophone [3] IASUS. TEN-4 Throat Mic & Speaker Amplifier Kit [Online] Available: https://shop.iasus-concepts.com/product/ten-4-throat-mic-speaker-amplifier-kit-black/ [4] G. Fant, Acoustic theory of speech production: with calculations based on X-ray studies of Russian articulations (no. 2). Walter de Gruyter, 1971. [5] G. Fant, "Glottal flow: models and interaction," Journal of Phonetics, vol. 14, no. 3-4, pp. 393-399, 1986. [6] J. Andrews, M. Adams, and T. Montenegro-Johnson, "A universal scaling law of mammalian touch," Science advances, vol. 6, no. 41, p. eabb6912, 2020. [7] L. Wu, K. Xiao, J. Dong, S. Wang, and M. Wan, "Measurement of the sound transmission characteristics of normal neck tissue using a reflectionless uniform tube," The Journal of the Acoustical Society of America, vol. 136, no. 1, pp. 350-356, 2014. [8] RØDE. VideoMIC NTG Datasheet [Online] Available: https://edge.rode.com//pdf/products/633/VMNTG%20DS%2003.pdf [9] H.-P. Liu, Y. Tsao, and C.-S. Fuh, "Bone-conducted speech enhancement using deep denoising autoencoder," Speech Communication, vol. 104, pp. 106-112, 2018. [10] A. Shahina and B. Yegnanarayana, "Mapping speech spectra from throat microphone to close-speaking microphone: A neural network approach," EURASIP Journal on Advances in Signal Processing, vol. 2007, pp. 1-10, 2007. [11] C. Yu, K.-H. Hung, S.-S. Wang, Y. Tsao, and J.-w. Hung, "Time-domain multi-modal bone/air conducted speech enhancement," IEEE Signal Processing Letters, vol. 27, pp. 1035-1039, 2020. [12] S. K. Paul, R. R. Paul, M. Nishimura, and M. E. Hamid, "Throat Microphone Speech Enhancement Using Machine Learning Technique," in International Conference on Innovative Computing and Cutting-edge Technologies, 2020: Springer, pp. 1-11. [13] M. Huang, "Development of taiwan mandarin hearing in noise test," Department of speech language pathology and audiology, Nation Taipei University of Nursing and Health Science, 2005. [14] R. Lundström, "Vibration exposure of the glabrous skin of the human hand," Umeå universitet, 1985. [15] M. Nolan, B. Madden, and E. Burke, "Accelerometer based measurement for the mapping of neck surface vibrations during vocalized speech," in 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009: IEEE, pp. 4453-4456. [16] M. Umatani et al., "Skin Acceleration Levels Estimated by a Neck-surface Accelerometer during Phonation Are Affected by The Mechanical Properties of The Anterior Cervical Skin," Journal of Voice, 2021. [17] ITU-T, "Methods for subjective determination of transmission quality," 1996. [18] C. H. Taal, R. C. Hendriks, R. Heusdens, and J. Jensen, "A short-time objective intelligibility measure for time-frequency weighted noisy speech," in 2010 IEEE international conference on acoustics, speech and signal processing, 2010: IEEE, pp. 4214-4217. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/90777 | - |
| dc.description.abstract | 利用高規格壓電加速度計，可以很好的接收喉部表面的振動訊號，並且具備很好的環境雜訊免疫力。結合機器學習的語音轉換技術，可以補償喉部振動訊號在高頻訊號調音缺失的問題。為了推進喉部振動麥克風的商業應用普及化，本文針對喉部振動的感測器進行探討，分析不同感測器對於語音訊號的影響，提出運用微機電加速度計來改善原本壓電式體積龐大以及造價昂貴的問題。同時，探討運用傳統的語音增強方法來改善以微機電加速度計為感測基礎的振動訊號，進一步提升語音轉換的品質。 | zh_TW |
| dc.description.abstract | By utilizing high-quality piezoelectric accelerometers, the vibrations on the neck surface can be effectively captured, which is exhibiting the excellent immunity to environmental noise. With machine-learning-based speech conversion techniques, it becomes possible to compensate for the loss of high-frequency components in the vibration signal. To promote the widespread commercial application of neck vibration microphones, this study dedicates to investigate the different sensors' impact on speech signals. And proposes the use of MEMS accelerometers as a replacement for piezoelectric types, in order to address the issues of size and cost. In addition, the study explores the application of conventional speech enhancement methods to improve the vibration signals captured by MEMS accelerometers, for enhancing the quality of speech conversion. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2023-10-03T17:34:22Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2023-10-03T17:34:22Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 誌謝 i
中文摘要 ii Abstract iii 第一章 緒論 1 1-1 研究背景 1 1-2 研究動機 2 第二章 基於喉部振動訊號之振動加速度麥克風聲音轉換系統 3 2-1 發聲原理 3 2-1-1 聲源過濾理論與喉部振動訊號濾波 3 2-1-2 聽覺特性 5 2-2 感測器介紹 6 2-2-1 傳統麥克風 6 2-2-2 振動加速度麥克風 7 2-3 振動加速度麥克風聲音轉換系統 13 2-3-1 訓練集資料擷取與預處理 14 2-3-2 AI振動加速度麥克風聲音轉換訓練階段 17 2-3-3 AI振動加速度麥克風聲音轉換階段 18 2-3-4 實驗架設以及流程 19 第三章 振動加速度麥克風之性能比較 21 3-1 喉部貼片位置分析 21 3-1-1 響度規範以及音節測試 22 3-2 振動加速度麥克風感測器比較 26 3-2-1 微機電振動加速度麥克風貼片製作 26 3-2-2 振動加速度麥克風訊雜比分析 27 3-2-3 振動加速度麥克風頻譜同調性分析 30 第四章 微機電振動加速度麥克風聲音轉換 32 4-1 語音品質評估方法 32 4-1-1 主觀式評估 32 4-1-2 客觀式評估 33 4-2 單通道振動加速度麥克風聲音轉換結果 33 4-2-1 基於機器學習空間複雜度的語音品質改善 36 4-3 基於語音增強算法的語音品質改善 37 4-3-1 單通道語音增強算法 38 4-3-2 多通道語音增強算法 44 第五章 結論與未來展望 49 5-1 語音增強算法的改進 49 參考文獻 50 附錄A-1: 不同喉部貼片位置的聲壓級以及表皮加速度級的散點圖 52 附錄A-2: 微機電振動加速度麥克風貼片 57 附錄A-3: 喉部振動訊號與麥克風訊號同調性分析 59 附錄B：模態局部化共振式加速度計的設計及驗證 67 B-1附錄簡介 67 B-2共振式加速度計介紹以及原理 67 B-2-1常規共振式加速度計原理 68 B-2-2模態局部化共振式加速度計 68 B-2-3模態局部化效應 69 B-3共振式加速度計設計分析 70 B-3-1共振器設計 70 B-3-2力量放大器設計 76 B-4耦合雙自由度共振器系統 81 B-4-1頻率偏移與量測方法 81 B-4-2靈敏度最佳化設計 83 B-4-3耦合剛性比例限制 85 B-4-4狀態空間分析 87 B-4-5 下線佈局示意圖 91 B-5實驗結果與討論 93 B-5-1量測架設 93 B-5-2元件頻率響應量測 94 B-5-3模擬與量測驗證比較 100 References 102 | - |
| dc.language.iso | zh_TW | - |
| dc.subject | 微機電加速度計 | zh_TW |
| dc.subject | 機器學習 | zh_TW |
| dc.subject | 語音轉換 | zh_TW |
| dc.subject | 喉部振動訊號 | zh_TW |
| dc.subject | 語音增強 | zh_TW |
| dc.subject | MEMS accelerometer | en |
| dc.subject | Machine learning | en |
| dc.subject | Speech enhancement | en |
| dc.subject | Throat vibration signal | en |
| dc.subject | Voice conversion | en |
| dc.title | 基於微機電加速度計之機器學習喉部振動語音轉換可行性研究 | zh_TW |
| dc.title | Feasibility Study of Machine-Learning Based Throat-Vibration-to-Voice Conversion Using MEMS Accelerometers | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 111-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 張培仁;李銘晃 | zh_TW |
| dc.contributor.oralexamcommittee | Pei-Zen Chang;Ming-Huang Li | en |
| dc.subject.keyword | 機器學習,語音轉換,喉部振動訊號,微機電加速度計,語音增強, | zh_TW |
| dc.subject.keyword | Machine learning,Voice conversion,Throat vibration signal,MEMS accelerometer,Speech enhancement, | en |
| dc.relation.page | 102 | - |
| dc.identifier.doi | 10.6342/NTU202303603 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2023-08-13 | - |
| dc.contributor.author-college | 工學院 | - |
| dc.contributor.author-dept | 應用力學研究所 | - |
| dc.date.embargo-lift | 2028-08-10 | - |
| 顯示於系所單位： | 應用力學研究所 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-111-2.pdf 此日期後於網路公開 2028-08-10 | 14.85 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。