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系統識別號 U0026-1308201820221400
論文名稱(中文) 高齡者陪伴機器人
論文名稱(英文) A Companion Robot for Elderly People
校院名稱 成功大學
系所名稱(中) 工程科學系
系所名稱(英) Department of Engineering Science
學年度 106
學期 2
出版年 107
研究生(中文) 陳旻甄
研究生(英文) Min-Chen Chen
學號 N96051384
學位類別 碩士
語文別 中文
論文頁數 76頁
口試委員 口試委員-王榮泰
口試委員-王宗一
口試委員-侯廷偉
口試委員-陳澤生
口試委員-吳村木
指導教授-周榮華
中文關鍵字 陪伴機器人  語音辨識  情緒辨識  希爾伯特黃轉換  支持向量機 
英文關鍵字 companion robot  speech recognition  emotion recognition  HHT  SVM 
學科別分類
中文摘要 本論文研製一款符合高齡者需求的陪伴機器人,並賦予機器人語音情緒辨識,以達到瞭解人類情緒並且撫慰人心的機器人。本論文與孫佾微同學之論文合作完成陪伴機器人,本文負責機器人語音辨識部分。為了實現符合高齡者需求的陪伴機器人,機器人會透過聽覺理解高齡者情緒,做出安撫情緒的語音回應以及表情動作,來達到撫慰高齡者的孤獨感以及悲傷。本文以語音辨識情緒,提出了一種基於希爾伯特-黃轉換的語音情感識別方法。有別於直接分析給定的語音訊號,使用EMD提取本質模態函數(IMF)和邊際頻譜。研究發現,對應於不同情緒的IMF個數和邊際頻譜值具有區別特徵,而以之做為辨識的特徵。為了強化辨識,使用支持向量機(SVM)進行情緒分類,對Emo-DB語音情感數據庫進行了模型訓練,該數據庫包含四種類別的情緒,即生氣、快樂、傷心和一般,總共103筆語音資料,最終獲得辨識率為84%。換言之,機器人可以獲得很好的情緒辨識以及與人的互動。
英文摘要 A companion robot was designed and implemented in this thesis for elderly who may be alone or feel lonely at home. The robot can recognize the emotion of the elderly through voice processing and comfort their hearts by using various motions. In the emotion recognition system, a speech emotion recognition method based on the Hilbert-Huang transform (HHT) was developed. Instead of directly analyzing a speech signal, HHT applies the empirical mode decomposition (EMD) to extract the intrinsic mode function (IMF) and combines the IMF feature, the number of IMFs, and the marginal spectrum to identify various emotion features embedded in the voice. These distinctive features and the associated statistical parameters were selected as the features for emotion recognition. In order to classify different emotions, the method of support vector machine (SVM) was used for emotion classification for which the Emo-DB speech emotion database was modeled first. The database contains four categories of emotions; namely, angry, happy, sad, and general. Then, the model was used for the present robot. The results show that the final recognition rate is 84%, indicating that the robot can recognize its user’s emotion and interact with its user reasonably well.
論文目次 中文摘要 I
Extended Abstract II
致謝 VIII
圖目錄 XIII
表目錄 XVII
第一章 序論 1
1.1 研究動機與目的 1
1.2 文獻回顧 4
1.2.1 陪伴機器人回顧 4
1.2.2 情緒辨識文獻回顧 7
1.2.3 對話機器人文獻回顧 14
1.3 研究貢獻 16
1.4 論文架構 16
第二章 系統架構與軟硬體介紹 18
2.1 陪伴機器人系統架構 18
2.2 系統硬體介紹 20
2.2.1 微處理器dsPIC30F4011 20
2.2.2 直流降壓模組 22
2.2.3 直流馬達 23
2.2.4 馬達驅動晶片TA7291P 25
2.2.5 光耦合晶片PC817 27
2.2.6 揚聲器、麥克風 28
2.2.7 4.3寸 HMI觸控液晶顯示模塊 30
2.3 機器人之機構設計 33
2.3.1 機器人內部 33
2.3.2 機器人頭部 35
2.3.3 機器人身體 35
2.4 軟體規格 36
第三章 對話機器人 38
3.1 Node.js 38
3.2 Dialogflow 39
3.3 命名實體識別 41
3.4 Express 42
3.5 Cordova 42
3.6 Ionic 43
3.7 AngularJS 44
3.8 對話機器人系統架構 44
第四章 情緒辨識 46
4.1 希爾伯特黃轉換(HHT) 46
4.2 經驗模態分解 47
4.3 希爾伯特轉換(Hilbert transform) 51
4.4 邊際譜(Marginal Spectrum) 52
4.5 支持向量機 53
第五章 程式流程規劃 55
5.1 整體軟體架構 55
5.2 對話機器人程式規劃 57
5.3 情緒辨識程式規劃 57
5.3.1 特徵選擇 57
5.3.2 模型訓練 62
5.3.3 辨識模型 63
第六章 結果和討論 64
6.1 情緒辨識結果和討論 64
6.1.1 特徵選擇 64
6.1.2 情緒辨識 66
6.2 機器人動作和語音回應結果 69
第七章 結論與未來展望 72
7.1 結論 72
7.2 建議 73
參考文獻 74
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