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研究生:陳宜佳
研究生(外文):CHEN, YI-CHIA
論文名稱:兒童和成人對真實臉孔的再認記憶優於人工智慧合成的臉孔
論文名稱(外文):Children and adults exhibit superior recognition memory for real faces than AI-synthesized faces
指導教授:簡惠玲簡惠玲引用關係
指導教授(外文):CHIEN, HUI-LIN
口試委員:許儷絹田意民簡惠玲
口試委員(外文):HSU, LI-CHUANTIEN, YI-MINCHIEN, HUI-LIN
口試日期:2024-01-17
學位類別:碩士
校院名稱:中國醫藥大學
系所名稱:生物醫學研究所碩士班
學門:生命科學學門
學類:生物化學學類
論文種類:學術論文
論文出版年:2024
畢業學年度:112
語文別:中文
論文頁數:66
中文關鍵詞:AI合成臉孔臉孔記憶種族效應劍橋臉孔記憶作業
外文關鍵詞:AI-synthesized faceold/new recognition taskface memoryCambridge Face Memory Task
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Nightingale和Farid (2022) 發現人們無法有效區分真實(real)的與生成對抗網路(GAN)合成(synthesized)的臉孔。然而,電腦生成的臉孔是否會影響人們對臉孔的記憶表現仍屬未知。本研究探討台灣成人和兒童對於真實和AI合成臉孔的記憶表現和發展趨勢,以及個體之記憶表現和劍橋臉孔記憶測驗得分間的關係。本研究招募25位成人(平均22.41歲)和72位兒童(平均8.08歲),兒童參與者再分為三個年齡組別: 4-7歲、8-9歲和10-12歲。每位參與者都接受劍橋臉孔記憶作業(Cambridge Face Memory task,CFMT)、新舊臉孔再認測驗 (Old/New Face Recognition Task),並在兩天後完成線上臉孔記憶問卷。新舊臉孔再認測驗有兩階段;學習階段有16張臉孔(8張合成、8張真實臉孔),測試階段有兩個回合,每回合各有32張臉孔(16張舊臉孔、16張新臉孔);主要依變項為再認正確率與反應時間。結果顯示無論是立即的再認或是兩天後的線上問卷,參與者對於真實臉孔的再認正確率均顯著高於合成臉孔(當日: Mreal =0.792 vs. Msynthetic =0.714; 二天後: Mreal =0.760 vs. Msynthetic =0.680);辨認真實臉孔的平均反應時間 (Mreal =1523ms)也顯著短於合成臉孔(Msy nthetic =1675ms)。其次,我們觀察到顯著的年齡發展趨勢,參與者的平均正確率隨年齡增長逐漸提高(4-7歲: M = 0.639, 8-9歲: M = 0.731, 10-12歲: M = 0.770, 成人: M = 0.831)。再者,所有參與者的CFMT得分與臉孔再認的平均正確率呈現顯著正相關(r=0.746)。最後,不論是兒童或成人都未呈現顯著的本種族優勢(own-race advantage)。總體而言,本研究揭示台灣人對真實臉孔的記憶再認正確率較高,反應速度也較快。而隨著年齡增加,人們對真實和合成臉孔的記憶表現都呈現持續進步的趨勢,表示臉孔記憶能力在兒童期有長足的發展。最後,參與者CFMT分數與臉孔再認作業表現指標間呈現顯著正相關,顯示這兩種測量作業可能觸及了類似的認知機制。
Nightingale and Farid (2022) reported that people were unable to distinguish between real and AI-synthesized faces (GAN-Syn faces). However, whether AI-generated deep-fake faces might affect people's memory is still an open question. This study investigated recognition memory for real versus AI-synthesized faces in Taiwanese children and adult and how individual’s memory performance may correlate with standardized face memory test. Twenty-five adults (mean age = 22.41) and 72 children (mean age = 8.80) joined the study. Children were divided into three age groups: 4-7, 8-9, and 10-11. Each participant underwent the Cambridge Face Memory Test (CFMT) and an Old/New Face Recognition Task during the lab visit, and completed an online face memory questionnaire two days later. The Old/New Face Recognition Task consisted of two phases. The learning phase included 16 faces (8 synthesized and 8 real faces). The testing phase consisted of two rounds, each with 32 faces (16 old and 16 new faces). The results showed that, across age, participants' recognition accuracy for real faces was significantly higher than synthetic faces, in the immediate test and the two-days-later questionnaire (1st day: Mreal =0.792 vs. Msynthetic =0.714; two days later: Mreal =0.760 vs. Msynthetic =0.680). Moreover, we observed a significant developmental progression that the mean accuracy gradually increased with age (4-7 yr-old: M = 0.639, 8-9 yr-old: M = 0.731, 10-12 yr-old: M = 0.770, Adult: M = 0.831). Third, we found a significant positive correlation between mean accuracy and CFMT score (r=0.746). Finally, the results did not demonstrate a significant own-race advantage. Overall, the present study reveals that Taiwanese individuals exhibit higher recognition accuracy and faster responses for real faces. Additionally, we observed a significant developmental progression in recognition memory that younger children did poorly with all tasks and gradually improve with age. Lastly, the positive correlation between individual’s CFMT scores and task performances indicates that both measurements may tap into similar cognitive mechanisms.
目 錄
第一章 緒論 1
第一節:臉孔辨認中的他種族效應 1
第二節:臉孔記憶在兒童期的發展 5
第三節:臉孔辨認的新挑戰: 難以辨別的AI合成的仿真臉孔 13
第四節:真實臉孔和類真實臉孔的不同神經處理 17
第五節:研究動機與目的 20
第二章 劍橋臉孔記憶(Cambridge Face Memory Task)線上測驗 22
第一節 研究參與者 22
第二節 作業內容與程序 23
第三章 真實與合成臉孔的新舊再認作業 26
第一節 研究參與者 26
第二節 實驗刺激與設備 26
第三節 實驗程序 28
第四節 實驗設計與統計分析 32
第四章 結果與統計分析 33
第一節 劍橋臉孔記憶測驗(CFMT) 33
第二節 真實與合成臉孔的新舊再認記憶作業 34
第三節 CFMT分數和新舊再認記憶作業表現指標的相關分析 44
第五章 綜合討論 51
第一節 真實臉孔相較合成臉孔展現更高正確率 51
第二節 臉孔記憶能力的發展支持晚熟論觀點 53
第三節 未發現原本預期的本種族臉孔優勢 55
第四節 劍橋臉孔記憶作業與臉孔再認能力的相關性探討 56
第五節 結論、限制與未來展望 57
參考文獻 58

圖 例
圖一:Sangrigoli等人於 2005所使用的實驗刺激與實驗結果
圖二:Weigelt等人於2014臉孔記憶與知覺作業的示意圖
圖三:Weigelt等人於2014的測驗結果圖
圖四:Chance等人於1982年的測試結果圖
圖五:Goodman等人於2007年的測試結果圖
圖六:Chien 等人 2018年研究的實驗刺激範例與作業示意圖
圖七:Chien 等人2018年的實驗結果
圖八:葉宇軒2019年TFMT與CFMT的結果
圖九:Nightingale & Farid (2022)所使用的實驗刺激臉孔
圖十:Nightingale & Farid (2022)實驗一與實驗二的結果
圖十一:Nightingale & Farid (2022)真實與合成臉孔的信任度評分結
果示意圖
圖十二 : Nightingale & Farid (2022)信任度評分最高與最低的範例
圖十三 : Wheatley等人(2011)年所使用的實驗刺激材料
圖十四 : Wheatley等人(2011)主要的ERP結果圖
圖十五 : Wheatley等人(2011)由不同實驗刺激所引起的ERP頭皮電位拓譜分布結果圖
圖十六 : Duchaine & Nakayama (2006)的劍橋臉孔記憶測驗的臉孔刺 激示意圖
圖十七 : 劍橋臉孔記憶測驗完成後的成績顯示畫面
圖十八 : 本論文臉孔再認作業所採用的刺激臉孔
圖十九 : 臉孔再認作業學習階段程序示意圖
圖二十 : 臉孔再認作業測試階段的程序示意圖
圖二十一 兩天後臉孔再認問卷的指導語和再認問卷題目示意圖
圖二十二 : 兒童與成人劍橋臉孔記憶測驗的平均正確百分比
圖二十三 : 不同年齡組對於真實與合成臉孔的平均正確率
圖二十四 : 所有年齡組在不同的測驗時間的平均正確率
圖二十五 : 不同種族臉孔在不同的測驗時間的平均正確率
圖二十六 : 不同年齡組對於真實與合成臉孔的平均反應時間
圖二十七 : 所有年齡組在不同的測驗時間的平均反應時間
圖二十八 : 不同年齡組對於真實與合成臉孔的平均d-Prime
圖二十九 : 所有年齡組在不同的測驗時間的平均d-Prime
圖三十 : 兒童與成人CFMT測驗分數與臉孔再認作業正確率相關圖
圖三十一 : CFMT分數與第一天的臉孔再認作業正確率的相關圖
圖三十二 : CFMT分數與兩天後的臉孔再認作業正確率的相關圖
圖三十三 : CFMT分數與第一天的臉孔再認作業d-Prime的相關圖
圖三十四 : CFMT分數與兩天後的臉孔再認作業d-Prime的相關圖
圖三十五 : Tanaka等人(1998) 提出非典型臉孔與典型臉孔在臉孔空間中不等距分布的示意圖

表 例
表一 : 劍橋臉孔記憶作業正確率變異數分析摘要表
表二 : 臉孔再認作業正確率變異數分析摘要表
表三 : 臉孔再認作業反應時間變異數分析摘要表
表四 : 臉孔再認作業d-Prime變異數分析摘要表
表五 : 參與者劍橋臉孔記憶測驗分數與臉孔再認作業正確率的相關係數表
表六 : 參與者劍橋臉孔記憶測驗分數與臉孔再認作業d-Prime的相關係數表






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