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研究生: 桂璿
Kuei, Hsuan
論文名稱: 用於學習場域之情境式即時語音追蹤與強化系統
A Situational Speech Tracking and Enhancement System for Student in Class
指導教授: 杜翌群
Du, Yi-Chun
學位類別: 碩士
Master
系所名稱: 工學院 - 生物醫學工程學系
Department of BioMedical Engineering
論文出版年: 2021
畢業學年度: 109
語文別: 英文
論文頁數: 65
中文關鍵詞: 電腦聽覺 、電腦視覺 、語音強化 、聽力損失 、注意力不足過動症
外文關鍵詞: computer hearing, computer vision, speech enhancement , hearing loss, Attention-Deficit/Hyperactivity Disorder
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  • 本研究提出整合聲音定位、電腦視覺技術與情境式的目標分析原則,打造可用於學習場域之可追蹤與強化目標語音的方法,並完成初步的穿戴式雛型系統。該雛型系統的使用對象著重於注意力不足過動症與有聽力受損的學生等,藉由系統強化學習環境中的目標語音並降低噪音干擾,提升學生在學習過程的專注力。本研究改良實驗室先前所提出之用於聽損人士的輔助聽力系統,導入聲音定位、新的陣列麥克風設計與情境式的分析原則,讓其更能符合學生在學習場域之需求;例如改善電腦視覺偵測不到人臉時無法定位目標、學習時的可能目標切換、學生如何穿戴的設計等。實驗結果顯示,本研究所提出的方法在噪音源與目標相隔30°以上,無論電腦視覺是否有偵測到人臉都能正常定位。其定位的準確度大於83%,且隨著距離收音端越遠其分辨率越高,並可提升目標語音至少5.2 dB。情境式的目標分析原則可讓學生選擇所對應的學習場景,讓使用上更有彈性。利用此方法所打造的學童穿戴式雛型產品設計,與市面上的產品相比有其優勢,且更能符合學童在學習環境中使用,顯示此方法未來在產品化的潛力。

    This research proposed to create a target speech tracking and enhancement method that could be used in the learning environment by integrating sound localization, computer vision technology and situational target analysis principles, and built a preliminary wearable prototype system. The prototype system was targeted at students with ADHD or hearing-impaired students. The system enhanced the target speech in the learning environment and reduced noise interference to help students concentrate more easily through the learning process. This research improved the previous assistive hearing system for the hearing impaired proposed by the laboratory by introducing sound localization, new array microphone design, and situational analysis principles, so that it could better meet the needs of students in the learning environment. For example, the proposed system solved the problem that the computer vision could not locate the target when the face was not detected, the possible target switching during learning, the design of how students wear it, etc. The experimental results show that the proposed method from this research could locate the noise source apart from the target more than 30°, regardless of whether the computer vision detected the human face or not. Its positioning accuracy was greater than 83%, and its success rate was higher as the distance from the microphone was farther, and the target voice could be improved by at least 5.2 dB. The situational target analysis principles allowed students to choose the corresponding learning scenario, making it more flexible in use. The wearable prototype design for schoolchildren had its advantages compared with other products on the market and could adapt to the learning environment well, showing the potential of this method in productization in the future.

    中文摘要 i Abstract ii Acknowledgements iii Table of Contents v List of Tables viii List of Figures ix List of Abbreviations xi Chapter 1: Introduction 1 1.1 Unmet needs 1 1.2 Symptoms of ADHD 1 1.2.1 Prevalence of ADHD 3 1.2.2 Etiologies of ADHD 4 1.2.3 Diagnostic Criteria of ADHD 5 1.2.4 Treatments of ADHD 6 1.3 Human Auditory System 8 1.3.1 Prevalence of Hearing Loss 9 1.3.2 Causes of Hearing Loss 9 1.3.3 The Disadvantage of Hearing Aids 11 1.4 Research Motivation and Purpose 11 1.5 Research Purpose 12 Chapter 2: Literature Review 13 2.1 Listening to SOI in Noisy Learning Environment 13 2.1.1 Noise Effects on Attention 17 2.1.2 Noise Effects on Academic Performance 19 2.1.3 Current Methods for SNR Enhancement in Class 20 2.2 Noise Effects on Learning of Students with ADHD 21 2.3 The Influence of Hearing Loss on Learning 23 2.4 Introduction to the Previous Study of the Proposed System 24 Chapter 3: Materials and Methods 28 3.1 The distributed stereo micro-array microphone architecture 28 3.1.1 Advanced self-adaptive beamforming algorithm 29 3.2 Situational Design 31 Chapter 4: Experimental Design and Results 36 4.1 Target Sound Source Detection of Computer Hearing from Different Locations 36 4.2 The Influence of Noise Source from Different Locations 38 4.3 Identification of Computer Vision from Different Face Angles 41 4.4 Comparison of Proposed and Previous Methods 43 Chapter 5: Discussion 46 Chapter 6: Conclusions and Future Works 52 References 54

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