請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/37303完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 曹承礎 | |
| dc.contributor.author | Li-Ying Chang | en |
| dc.contributor.author | 張立穎 | zh_TW |
| dc.date.accessioned | 2021-06-13T15:23:52Z | - |
| dc.date.available | 2009-07-30 | |
| dc.date.copyright | 2008-07-30 | |
| dc.date.issued | 2008 | |
| dc.date.submitted | 2008-07-21 | |
| dc.identifier.citation | [1] C. Shaw and J. Ivens, Building great customer experiences: Palgrave Macmillan, Basingstoke, 2002.
[2] N. Millard, 'Learning from the ‘wow’factor—how to engage customers through the design of effective affective customer experiences,' BT Technology Journal, vol. 24, pp. 11-16, 2006. [3] B. J. Pine 2nd and J. H. Gilmore, 'Welcome to the experience economy,' Harv Bus Rev, vol. 76, pp. 97-105, 1998. [4] L. P. Carbone, 'Clued In: How to Keep Customers Coming Back Again and Again,' Financial Times Prentice Hall, 2004. [5] B. Schmitt, Customer Experience Management: A Revolutionary Approach to Connecting with Your Customers: Wiley, 2003. [6] G. Zaltman, How Customers Think: Essential Insights Into the Mind of the Market: Harvard Business School Press, 2003. [7] J. Trigger and M. Harrison, 'Six steps to excellent customer service,' BT Technology Journal, vol. 24, pp. 117-126, 2006. [8] A. R. Damasio, Descartes'error: emotion, reason, and the human brain: New York: GP Putnam, 1994. [9] K. Dawson, The Call Center Handbook: The Complete Guide to Starting, Running, and Improving Your Call Center: Cmp Books, 2003. [10] M. Sargent, 'Customer service is the name of this game.,' in Communication News, 2001, p. 54. [11] J. Carlzon, Moments of truth: Ballinger Pub. Co Cambridge, Mass, 1987. [12] E. Delorey, 'Correlating IVR Performance and Customer Satisfaction,' May, 2003. [13] A. Jon, 'Call center management by the numbers,' Purdue Umversity Pre~ s, 1997. [14] L. Devillers, L. Vidrascu, and L. Lamel, 'Challenges in real-life emotion annotation and machine learning based detection,' Neural Networks, vol. 18, pp. 407-422, 2005. [15] P. Ekman, 'An Argument for Basic Emotions,' Emotion: Themes in the Philosophy of the Mind, 2005. [16] C. M. Lee and S. S. Narayanan, 'Toward detecting emotions in spoken dialogs,' Speech and Audio Processing, IEEE Transactions on, vol. 13, pp. 293-303, 2005. [17] I. Shafran, M. Riley, and M. Mohri, 'Voice signatures,' Automatic Speech Recognition and Understanding, 2003. ASRU'03. 2003 IEEE Workshop on, pp. 31-36. [18] C. M. Lee, S. S. Narayanan, and R. Pieraccini, 'Combining Acoustic and Language Information for Emotion Recognition,' 2002. [19] D. J. Litman and K. Forbes-Riley, 'Recognizing student emotions and attitudes on the basis of utterances in spoken tutoring dialogues with both human and computer tutors,' Speech Communication, vol. 48, pp. 559-590, 2006. [20] A. Batliner, K. Fischer, R. Huber, J. Spilker, and E. Noth, 'Desperately Seeking Emotions or: Actors, Wizards, and Human Beings,' 2000. [21] R. Tato, R. Santos, R. Kompe, and J. M. Pardo, 'Emotional Space Improves Emotion Recognition,' 2002. [22] R. Cowie and R. R. Cornelius, 'Describing the emotional states that are expressed in speech,' Speech Communication, vol. 40, pp. 5-32, 2003. [23] L. Devillers, L. Lamel, I. Vasilescu, C. Limsi, and F. Orsay, 'Emotion detection in task-oriented spoken dialogues,' Multimedia and Expo, 2003. ICME'03. Proceedings. 2003 International Conference on, vol. 3, 2003. [24] C. Pereira, 'Dimensions of emotional meaning in speech,' 2000. [25] R. Plutchik, The psychology and biology of emotion: HarperCollins College Publishers, New York, NY, 1994. [26] M. Shami and W. Verhelst, 'An evaluation of the robustness of existing supervised machine learning approaches to the classification of emotions in speech,' Speech Communication, vol. 49, pp. 201-212, 2007. [27] P. Boersma, 'Praat, a system for doing phonetics by computer,' Glot International, vol. 5, pp. 341-345, 2001. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/37303 | - |
| dc.description.abstract | 現今競爭激烈、以顧客為導向的市場，成功的企業不僅藉由商品與服務吸引顧客，
還必須創造良好的顧客體驗環境，使顧客在理智與情感的層面皆獲得滿足，藉此提高 顧客對於服務、對於企業的滿意度，最終達到增加顧客忠誠度與提高企業價值的目的。 顧客體驗是顧客在消費過程中，對於服務人員和銷售商品互動的情感體認，客服中心 不僅是企業提供服務的一環，也是顧客體驗環境中的議題。本研究針對客服中心顧客 經驗管理，藉由偵測顧客於客服電話中每次往來發言的情緒，分析顧客於客服電話過 程中的體驗。 目前語音情緒辨識相關研究，主要透過聲學特徵（Acoustic Information），結合 語言學方面之詞彙特徵，以及語料背景特徵辨識情緒，辨識上往往必須以人工操作許 多資料前處理，且由於透過扮演式語料訓練系統，其結果於自然對話之情緒辨認之效 能並不如預期。 本研究之客服中心語音情緒辨識系統，在辨識語音情緒自動化流程目標下，利用 自然式語音資料訓練系統，同時實行動態參數選取方法，針對不同訓練資料以不同參 數辨識。同時，考量不同發言者表達情緒不同，以個人量化特徵值作為參數進行辨識。 所得最佳正確率(Precision Rate)以及召回率(Recall Rate)分別為76%以及82%，和 現有系統與文獻相比，皆有不錯表現，同時驗證個人量化之語音特徵值，比之未量化 之語音特徵值，的確能增進語音情緒辨識效能。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2021-06-13T15:23:52Z (GMT). No. of bitstreams: 1 ntu-97-R95725014-1.pdf: 920565 bytes, checksum: d46443def90cd7e044a64507b917dcdb (MD5) Previous issue date: 2008 | en |
| dc.description.tableofcontents | 表目錄 ........................................................................................................ 九
圖目錄 .................................................................................................... 一〇 第一章 緒論 ............................................................................................. 1 第一節 研究背景與動機 ..................................................................................... 1 第二節 研究目的 ................................................................................................. 4 第三節 論文架構 ................................................................................................. 5 第二章 文獻探討 ..................................................................................... 7 第一節 顧客經驗管理 ......................................................................................... 7 第二節 客服中心 ............................................................................................... 10 第三節 語音情緒辨識 ....................................................................................... 13 2.3.1 情緒分類與標示 ............................................................................ 13 2.3.2 語料來源 ........................................................................................ 15 2.3.3 辨識特徵 ........................................................................................ 17 2.3.4 分類器 ............................................................................................ 19 第三章 研究架構 ................................................................................... 21 第一節 系統架構 ............................................................................................... 21 第二節 設計目標 ............................................................................................... 22 第三節 解決方法 ............................................................................................... 24 第四章 系統實作 ................................................................................... 28 第一節 系統使用情境與流程 ........................................................................... 28 第二節 系統開發工具 ....................................................................................... 29 第五章 實驗設計與實驗結果分析 ....................................................... 31 第一節 實驗目的與設計 ................................................................................... 31 5.1.1 辨識正確率計算 ............................................................................ 32 5.1.2 K 折交叉驗證法 ............................................................................. 34 5.1.3 語音資料處理 ................................................................................ 35 第二節 實驗結果 ............................................................................................... 38 5.2.1 語論相似度計算 ............................................................................ 39 5.2.2 最近鄰居分類法k 值 .................................................................... 40 八 5.2.3 最佳特徵組合 ................................................................................ 41 5.2.4 個人化特徵值辨識效能 ................................................................ 42 第六章 結論與未來展望 ....................................................................... 44 第一節 結論 ....................................................................................................... 44 第二節 研究限制 ............................................................................................... 45 第三節 未來展望 ............................................................................................... 46 第七章 參考文獻 ................................................................................... 47 | |
| dc.language.iso | zh-TW | |
| dc.subject | 最近鄰居分類法 | zh_TW |
| dc.subject | 情緒辨識 | zh_TW |
| dc.subject | 顧客經驗管理 | zh_TW |
| dc.subject | k Nearest Neighbor | en |
| dc.subject | Customer Experience Management | en |
| dc.subject | Emotion Recognition | en |
| dc.title | 以語音情緒辨識系統落實客服中心顧客經驗管理 | zh_TW |
| dc.title | Customer Experience Management for Contact Center through Emotion Recognition System in Speech | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 96-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳建錦,林俊叡 | |
| dc.subject.keyword | 情緒辨識,顧客經驗管理,最近鄰居分類法, | zh_TW |
| dc.subject.keyword | Emotion Recognition,Customer Experience Management,k Nearest Neighbor, | en |
| dc.relation.page | 48 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2008-07-22 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
| 顯示於系所單位： | 資訊管理學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-97-1.pdf 未授權公開取用 | 898.99 kB | 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。