published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

by Kwok Chak Hung. / Thesis (M.Ph.)--Chinese University of Hong Kong

譚英隆 = Chinese input systems : a comparative study of Cantonese ... / Thesis (M.A.)--香港中文大學. / Manuscript. / Tan Yinglong = Chinese input systems : a comparative study of Cantonese ... / Thesis (M.A.)--Xianggang Zhong wen da xue. / 摘要 --- p.1 / Chapter 第一章 --- 問題背景 --- p.3 / 資訊處理的重要性 --- p.3 / 資訊處理在漢字社會所遇到的困難 --- p.5 / 香港中文資訊處理的需要 --- p.7 / 中文電腦在香港的使用現況 --- p.9 / 中文輸入法在香港的現況 --- p.10 / 普及漢字輸入法的重要性 --- p.13 / 本研究的內容和目的 --- p.15 / 本研究在教育上的意義 --- p.19 / Chapter 第二章 --- 文獻評述 --- p.22 / 電腦中文化 --- p.22 / 漢字的屬性 --- p.22 / 中文輸入法的兩大形式 --- p.24 / 中文鍵盤輸入法的類別 --- p.28 / 漢字輸入編碼的種類 --- p.31 / 字根編碼輸入 --- p.33 / 角形代碼輸入 --- p.36 / 筆劃編碼輸入 --- p.38 / 香港運科國際有限公司的基本筆劃編碼法 --- p.45 / 本研究的基本筆劃編碼法 --- p.47 / 拼音輸入法 --- p.49 / 廣東拼音輸入法 --- p.57 / 廣東拼音的注意符號 --- p.59 / 香港慣用的廣東注音符號 --- p.62 / 較近代的字書所採用的廣東注音符號 --- p.64 / 超群電腦公司廣東拼音輸入法所採用的注音符號 --- p.66 / 聲調的標注 --- p.68 / 中文輸入法的評估 --- p.70 / 1984年在上海進行的中文輸入編碼評測 --- p.72 / 資訊工業策進會1983年所作的評測 --- p.73 / 1985年台灣國立清華大學方聖平等人所作的評測 --- p.76 / 1987年台灣資訊工業策進會的測試 --- p.78 / 幾次主要評測的評述 --- p.81 / Chapter 第三章 --- 研究設計 --- p.86 / 簡述 --- p.86 / 受測試的中文輸入法 --- p.86 / 受試者 --- p.87 / 研究範圍 --- p.89 / 見字編碼和不見字編碼 --- p.92 / 教學和測驗進程 --- p.93 / 廣東拼音輸入法的教學 --- p.94 / 基本筆劃輸入法的教學 --- p.95 / 測量工具 --- p.96 / 測驗字的選取 --- p.98 / 資料分析 --- p.100 / Chapter 第四章 --- 結果及討論 --- p.108 / 三次測驗的總平均成績 --- p.108 / 總平均成績的進步情況 --- p.109 / 見字編碼測驗的平均成績 --- p.111 / 見字編碼部份的進步情況 --- p.112 / 聽字編碼測驗的平均成績 --- p.113 / 聽字編碼測驗的進步情況 --- p.115 / 輸入法與測驗法的關係 --- p.117 / 兩種輸入法學習難易的比較 --- p.118 / 錯誤類型統計 --- p.120 / 錯誤出現的頻率 --- p.121 / 廣東拼音輸入法最常見的錯誤 --- p.123 / 基本筆劃輸入法的取常見錯誤 --- p.131 / 從實驗結果比較兩種輸入法的學習歷程 --- p.136 / 已有知識的比較 --- p.137 / 其他知識對學習的干擾 --- p.138 / 記憶量的比較 --- p.143 / 規則難度的比較 --- p.145 / 規則變異的比較 --- p.151 / 從使用者的不同要求看兩種輸入法不同的特性 --- p.151 / 針對兩種輸入法特點的一些改良建議 --- p.153 / 見字輸入和聽字輸入 --- p.157 / 總結 --- p.158 / Chapter 第五章 --- 研究的限制 --- p.160 / 對機操作 --- p.160 / 完整的學習曲線 --- p.161 / 受試者 --- p.161 / 研究裡所採用的教學設計 --- p.162 / Chapter 圖一 --- 三次測驗的總成績 --- p.110 / Chapter 圖二 --- 三次見字編碼測驗的成績 --- p.113 / Chapter 圖三 --- 聽字編碼測驗的成績 --- p.116 / Chapter 圖四 --- 根據學習歷史和一般學習曲線的常態推斷的基本筆劃輸入法和廣東拚音 --- p.150 / Chapter 表一 --- 三次測驗的總平均成績 --- p.109 / Chapter 表二 --- 總平均成績的進步幅度 --- p.110 / Chapter 表三 --- 見字編碼測驗的成績 --- p.111 / Chapter 表四 --- 見字編碼測驗的進步幅度 --- p.113 / Chapter 表五 --- 聽字編碼測驗的成績 --- p.115 / Chapter 表六 --- 聽字編碼測驗的進步幅度 --- p.116 / Chapter 表七 --- 兩種輸入法在不同測驗法中的成績差異 --- p.117 / Chapter 表八 --- 廣東拚音輸入法最常見的二十種錯誤 --- p.123 / Chapter 表九 --- 引致各項錯誤的原因分析 --- p.129 / Chapter 表十 --- 基本筆劃輸入法最常見的二十種錯誤 --- p.131 / Chapter 表十一 --- 出現最多的二十種錯誤和它們所牽涉的錯誤類型 --- p.134 / 參考書目 / Chapter 附錄一 --- 基本筆劃輸入法教案 / Chapter 附錄二 --- 廣東拼音輸入法教案 / Chapter 附錄三 --- 測驗題目樣本 / Chapter 附錄四 --- 錯誤類型統計表

Cheang Sio Man. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1990. / Bibliography: leaves [103-106] / Chapter 1. --- THE EMERGENCE OF WINDOW SYSTEMS --- p.1-1 / Chapter 2. --- THE NEED OF A CHINESE WINDOW SYSTEM --- p.2-1 / Chapter 3. --- REQUIREMENTS AND DIFFICULTIES OF DEVELOPING A CHINESE WINDOW SYSTEM --- p.3-1 / Chapter 3.1. --- Input Method and Character Encoding --- p.3-1 / Chapter 3.2. --- Layout Direction and Formatting Mechanism --- p.3-3 / Chapter 3.3. --- Fonts --- p.3-3 / Chapter 3.3.1. --- Bitmap font --- p.3-4 / Chapter 3.3.2. --- Outline font --- p.3-6 / Chapter 4. --- A TRIAL TO OVERCOME THE DIFFICULTIES IN SUPPORTING CHINESE FONTS - OVERVIEW OF A CHINESE FONT SERVER SYSTEM --- p.4-1 / Chapter 4.1. --- Network Font Server --- p.4-3 / Chapter 4.2. --- Local Font Server --- p.4-4 / Chapter 4.3. --- Fonts --- p.4-5 / Chapter 4.3.1. --- Bitmap font --- p.4-5 / Chapter 4.3.1. --- Outline font --- p.4-5 / Chapter 4.4. --- Caching --- p.4-6 / Chapter 5. --- ORGANIZATION OF THE CHINESE FONT SERVER SYSTEM --- p.5-1 / Chapter 5.1. --- Communication Module --- p.5-2 / Chapter 5.1.1. --- Client connection request channel --- p.5-3 / Chapter 5.1.2. --- Client communication channels --- p.5-3 / Chapter 5.1.3. --- Network server connection channel --- p.5-4 / Chapter 5.2. --- Client Service Module --- p.5-7 / Chapter 5.2.1. --- Font manipulation module --- p.5-7 / Chapter 5.2.1.1. --- Request to open a new font --- p.5-8 / Chapter 5.2.1.2. --- Request to close an opened font --- p.5-8 / Chapter 5.2.1.3. --- Request to load a font character --- p.5-9 / Chapter 5.2.2. --- Cache module --- p.5-10 / Chapter 6. --- FROM THE CHINESE FONT SERVER SYSTEM TO A CHINESE WINDOW SYSTEM --- p.6-4 / Chapter 7. --- SCREEN FONTS --- p.7-1 / Chapter 7.1. --- Hand-edit --- p.7-3 / Chapter 7.2. --- Bitmap Scaling --- p.7-3 / Chapter 7.3. --- Outline Scaling --- p.7-5 / Chapter 7.4. --- Manual Refinement --- p.7-16 / Chapter 8. --- FONT CACHING --- p.8-1 / Chapter 8.1. --- Font Caching Strategies --- p.8-1 / Chapter 8.1.1. --- Pre-loading --- p.8-1 / Chapter 8.1.2. --- Fix-loading --- p.8-4 / Chapter 8.1.3. --- Demand loading --- p.8-6 / Chapter 8.1.3.1. --- Least Recently Used (LRU) replacement --- p.8-9 / Chapter 8.1.3.2. --- Least Frequently Used (LFU) replacement --- p.8-9 / Chapter 8.1.4. --- Hybrid loading --- p.8-16 / Chapter 8.2. --- Retrieval Method --- p.8-22 / Chapter 8.2.1. --- Binary searching --- p.8-22 / Chapter 8.2.2. --- Tree searching --- p.8-24 / Chapter 8.2.3. --- Hash searching --- p.8 26 / Chapter 8.3. --- Cache Expansion and Retraction --- p.8-33 / Chapter 9. --- AN EXPERIMENTAL CHINESE FONT SERVER SYSTEM - CAPABILITIES AND RESTRICTIONS --- p.9-1 / Chapter 9.1. --- Experimental Servers --- p.9-1 / Chapter 9.2. --- Programming Interfaces --- p.9-3 / Chapter 9.2.1. --- Connection request --- p.9-3 / Chapter 9.2.2. --- Open and close fonts --- p.9-4 / Chapter 9.2.3. --- Request to load cache --- p.9-5 / Chapter 9.2.4. --- Change the current font --- p.9-5 / Chapter 9.2.5. --- Request a font character --- p.9-5 / Chapter 9.3. --- Testing Applications --- p.9-6 / Chapter 9.4. --- Statistics --- p.9-8 / Chapter 9.4.1. --- Cache performance --- p.9-8 / Chapter 9.4.1.1. --- Tests --- p.9-8 / Chapter 9.4.1.2. --- Results --- p.9-10 / Chapter 9.4.1.3. --- Discussion --- p.9-10 / Chapter 9.4.2. --- Local Server Vs. Network Server --- p.9-12 / Chapter 9.4.2.1. --- Tests --- p.9-12 / Chapter 9.4.2.2. --- Results --- p.9-13 / Chapter 9.4.2.3. --- Discussion --- p.9-13 / Chapter 9.4.3. --- Outline Font --- p.9-14 / Chapter 9.4.3.1. --- Tests --- p.9-14 / Chapter 9.4.3.2. --- Results --- p.9-14 / Chapter 9.4.3.3. --- Discussion --- p.9-15 / Chapter 10. --- EPILOGUE --- p.10-1 / Chapter 10.1. --- Conclusion --- p.10-1 / Chapter 10.2. --- Future Extension --- p.10-2

Thesis (M.Phil.)--Chinese University of Hong Kong. / Bibliography: leaves 45.

Wong Chi Yin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 107-114). / Abstract also in Chinese. / Abstract --- p.ii / Acknowledgements --- p.vi / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Introduction to Chinese IR --- p.1 / Chapter 1.2 --- Contributions --- p.3 / Chapter 1.3 --- Organization of this Thesis --- p.5 / Chapter 2 --- Background --- p.6 / Chapter 2.1 --- Indexing methods --- p.6 / Chapter 2.1.1 --- Full-text scanning --- p.7 / Chapter 2.1.2 --- Inverted files --- p.7 / Chapter 2.1.3 --- Signature files --- p.9 / Chapter 2.1.4 --- Clustering --- p.10 / Chapter 2.2 --- Information Retrieval Models --- p.10 / Chapter 2.2.1 --- Boolean model --- p.11 / Chapter 2.2.2 --- Vector space model --- p.11 / Chapter 2.2.3 --- Probabilistic model --- p.13 / Chapter 2.2.4 --- Logical model --- p.14 / Chapter 3 --- Investigation of Segmentation on the Vector Space Retrieval Model --- p.15 / Chapter 3.1 --- Segmentation of Chinese Texts --- p.16 / Chapter 3.1.1 --- Character-based segmentation --- p.16 / Chapter 3.1.2 --- Word-based segmentation --- p.18 / Chapter 3.1.3 --- N-Gram segmentation --- p.21 / Chapter 3.2 --- Performance Evaluation of Three Segmentation Approaches --- p.23 / Chapter 3.2.1 --- Experimental Setup --- p.23 / Chapter 3.2.2 --- Experimental Results --- p.24 / Chapter 3.2.3 --- Discussion --- p.29 / Chapter 4 --- Signature File Background --- p.32 / Chapter 4.1 --- Superimposed coding --- p.34 / Chapter 4.2 --- False drop probability --- p.36 / Chapter 5 --- Partitioned Signature File Based On Chinese Word Length --- p.39 / Chapter 5.1 --- Fixed Weight Block (FWB) Signature File --- p.41 / Chapter 5.2 --- Overview of PSFC --- p.45 / Chapter 5.3 --- Design Considerations --- p.50 / Chapter 6 --- New Hashing Techniques for Partitioned Signature Files --- p.59 / Chapter 6.1 --- Direct Division Method --- p.61 / Chapter 6.2 --- Random Number Assisted Division Method --- p.62 / Chapter 6.3 --- Frequency-based hashing method --- p.64 / Chapter 6.4 --- Chinese character-based hashing method --- p.68 / Chapter 7 --- Experiments and Results --- p.72 / Chapter 7.1 --- Performance evaluation of partitioned signature file based on Chi- nese word length --- p.74 / Chapter 7.1.1 --- Retrieval Performance --- p.75 / Chapter 7.1.2 --- Signature Reduction Ratio --- p.77 / Chapter 7.1.3 --- Storage Requirement --- p.79 / Chapter 7.1.4 --- Discussion --- p.81 / Chapter 7.2 --- Performance evaluation of different dynamic signature generation methods --- p.82 / Chapter 7.2.1 --- Collision --- p.84 / Chapter 7.2.2 --- Retrieval Performance --- p.86 / Chapter 7.2.3 --- Discussion --- p.89 / Chapter 8 --- Conclusions and Future Work --- p.91 / Chapter 8.1 --- Conclusions --- p.91 / Chapter 8.2 --- Future work --- p.95 / Chapter A --- Notations of Signature Files --- p.96 / Chapter B --- False Drop Probability --- p.98 / Chapter C --- Experimental Results --- p.103 / Bibliography --- p.107

by Leung Chi Hong. / Thesis (Ph.D.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 163-171). / Chapter Chapter 1. --- Introduction --- p.1 / Chapter Chapter 2. --- Background Study of Natural Language Processing --- p.9 / Chapter 2.1. --- Knowledge-based approach --- p.9 / Chapter 2.1.1. --- Morphological analysis --- p.10 / Chapter 2.1.2. --- Syntactic parsing --- p.11 / Chapter 2.1.3. --- Semantic parsing --- p.16 / Chapter 2.1.3.1. --- Semantic grammar --- p.19 / Chapter 2.1.3.2. --- Case grammar --- p.20 / Chapter 2.1.4. --- Problems of knowledge acquisition in knowledge-based approach --- p.22 / Chapter 2.2. --- Corpus-based approach --- p.23 / Chapter 2.2.1. --- Beginning of corpus-based approach --- p.23 / Chapter 2.2.2. --- An example of corpus-based application: word tagging --- p.25 / Chapter 2.2.3. --- Annotated corpus --- p.26 / Chapter 2.2.4. --- State of the art in the corpus-based approach --- p.26 / Chapter 2.3. --- Knowledge-based approach versus corpus-based approach --- p.28 / Chapter 2.4. --- Co-operation between two different approaches --- p.32 / Chapter Chapter 3. --- Induction Learning applied to Corpus-based Approach --- p.35 / Chapter 3.1. --- General model of traditional corpus-based approach --- p.36 / Chapter 3.1.1. --- Division of a problem into a number of sub-problems --- p.36 / Chapter 3.1.2. --- Solution selected from a set of predefined choices --- p.36 / Chapter 3.1.3. --- Solution selection based on a particular kind of linguistic entity --- p.37 / Chapter 3.1.4. --- Statistical correlations between solutions and linguistic entities --- p.37 / Chapter 3.1.5. --- Prediction of the best solution based on statistical correlations --- p.38 / Chapter 3.2. --- First problem in the corpus-based approach: Irrelevance in the corpus --- p.39 / Chapter 3.3. --- Induction learning --- p.41 / Chapter 3.3.1. --- General issues about induction learning --- p.41 / Chapter 3.3.2. --- Reasons of using induction learning in the corpus-based approach --- p.43 / Chapter 3.3.3. --- General model of corpus-based induction learning approach --- p.45 / Chapter 3.3.3.1. --- Preparation of positive corpus and negative corpus --- p.45 / Chapter 3.3.3.2. --- Statistical correlations between solutions and linguistic entities --- p.46 / Chapter 3.3.3.3. --- Combination of the statistical correlations obtained from the positive and negative corpora --- p.48 / Chapter 3.4. --- Second problem in the corpus-based approach: Modification of initial probabilistic approximations --- p.50 / Chapter 3.5. --- Learning feedback modification --- p.52 / Chapter 3.5.1. --- Determination of which correlation scores to be modified --- p.52 / Chapter 3.5.2. --- Determination of the magnitude of modification --- p.53 / Chapter 3.5.3. --- An general algorithm of learning feedback modification --- p.56 / Chapter Chapter 4. --- Identification of Phrases and Templates in Domain-specific Chinese Texts --- p.59 / Chapter 4.1. --- Analysis of the problem solved by the traditional corpus-based approach --- p.61 / Chapter 4.2. --- Phrase identification based on positive and negative corpora --- p.63 / Chapter 4.3. --- Phrase identification procedure --- p.64 / Chapter 4.3.1. --- Step 1: Phrase seed identification --- p.65 / Chapter 4.3.2. --- Step 2: Phrase construction from phrase seeds --- p.65 / Chapter 4.4. --- Template identification procedure --- p.67 / Chapter 4.5. --- Experiment and result --- p.70 / Chapter 4.5.1. --- Testing data --- p.70 / Chapter 4.5.2. --- Details of experiments --- p.71 / Chapter 4.5.3. --- Experimental results --- p.72 / Chapter 4.5.3.1. --- Phrases and templates identified in financial news articles --- p.72 / Chapter 4.5.3.2. --- Phrases and templates identified in political news articles --- p.73 / Chapter 4.6. --- Conclusion --- p.74 / Chapter Chapter 5. --- A Corpus-based Induction Learning Approach to Improving the Accuracy of Chinese Word Segmentation --- p.76 / Chapter 5.1. --- Background of Chinese word segmentation --- p.77 / Chapter 5.2. --- Typical methods of Chinese word segmentation --- p.78 / Chapter 5.2.1. --- Syntactic and semantic approach --- p.78 / Chapter 5.2.2. --- Statistical approach --- p.79 / Chapter 5.2.3. --- Heuristic approach --- p.81 / Chapter 5.3. --- Problems in word segmentation --- p.82 / Chapter 5.3.1. --- Chinese word definition --- p.82 / Chapter 5.3.2. --- Word dictionary --- p.83 / Chapter 5.3.3. --- Word segmentation ambiguity --- p.84 / Chapter 5.4. --- Corpus-based induction learning approach to improving word segmentation accuracy --- p.86 / Chapter 5.4.1. --- Rationale of approach --- p.87 / Chapter 5.4.2. --- Method of constructing modification rules --- p.89 / Chapter 5.5. --- Experiment and results --- p.94 / Chapter 5.6. --- Characteristics of modification rules constructed in experiment --- p.96 / Chapter 5.7. --- Experiment constructing rules for compound words with suffixes --- p.98 / Chapter 5.8. --- Relationship between modification frequency and Zipfs first law --- p.99 / Chapter 5.9. --- Problems in the approach --- p.100 / Chapter 5.10. --- Conclusion --- p.101 / Chapter Chapter 6. --- Corpus-based Induction Learning Approach to Automatic Indexing of Controlled Index Terms --- p.103 / Chapter 6.1. --- Background of automatic indexing --- p.103 / Chapter 6.1.1. --- Definition of index term and indexing --- p.103 / Chapter 6.1.2. --- Manual indexing versus automatic indexing --- p.105 / Chapter 6.1.3. --- Different approaches to automatic indexing --- p.107 / Chapter 6.2. --- Corpus-based induction learning approach to automatic indexing --- p.109 / Chapter 6.2.1. --- Fundamental concept about corpus-based automatic indexing --- p.110 / Chapter 6.2.2. --- Procedure of automatic indexing --- p.111 / Chapter 6.2.2.1. --- Learning process --- p.112 / Chapter 6.2.2.2. --- Indexing process --- p.118 / Chapter 6.3. --- Experiments of corpus-based induction learning approach to automatic indexing --- p.118 / Chapter 6.3.1. --- An experiment evaluating the complete procedures --- p.119 / Chapter 6.3.1.1. --- Testing data used in the experiment --- p.119 / Chapter 6.3.1.2. --- Details of the experiment --- p.119 / Chapter 6.3.1.3. --- Experimental result --- p.121 / Chapter 6.3.2. --- An experiment comparing with the traditional approach --- p.122 / Chapter 6.3.3. --- An experiment determining the optimal indexing score threshold --- p.124 / Chapter 6.3.4. --- An experiment measuring the precision and recall of indexing performance --- p.127 / Chapter 6.4. --- Learning feedback modification --- p.128 / Chapter 6.4.1. --- Positive feedback --- p.129 / Chapter 6.4.2. --- Negative feedback --- p.131 / Chapter 6.4.3. --- Change of indexed proportions of positive/negative training corpus in feedback iterations --- p.132 / Chapter 6.4.4. --- An experiment evaluating the learning feedback modification --- p.134 / Chapter 6.4.5. --- An experiment testing the significance factor in merging process --- p.136 / Chapter 6.5. --- Conclusion --- p.138 / Chapter Chapter 7. --- Conclusion --- p.140 / Appendix A: Some examples of identified phrases in financial news articles --- p.149 / Appendix B: Some examples of identified templates in financial news articles --- p.150 / Appendix C: Some examples of texts containing the templates in financial news articles --- p.151 / Appendix D: Some examples of identified phrases in political news articles --- p.152 / Appendix E: Some examples of identified templates in political news articles --- p.153 / Appendix F: Some examples of texts containing the templates in political news articles --- p.154 / Appendix G: Syntactic tags used in word segmentation modification rule experiment --- p.155 / Appendix H: An example of semantic approach to automatic indexing --- p.156 / Appendix I: An example of syntactic approach to automatic indexing --- p.158 / Appendix J: Samples of INSPEC and MEDLINE Records --- p.161 / Appendix K: Examples of Promoting and Demoting Words --- p.162 / References --- p.163

published_or_final_version / Computer Science / Master / Master of Philosophy

by Tong Po-Cheung. / Bibliography: leaves [v-10]-[v-11] / Thesis (M.Ph.)--Chinese University of Hong Kong, 1983

胡承慈. / 大字複印本. / Thesis (M.A.)--香港中文大學研究院電子計算學部. / Da zi fu yin ben. / Includes bibliographical references (leaves 26-27 (2nd group)). / Hu Chengci. / Thesis (M.A.)--Xianggang Zhong wen da xue yan jiu yuan dian zi ji suan xue bu. / 嗚謝 --- p.I / ABSTRACT --- p.II / 提要 --- p.III / Chapter 第一章 --- 緒論 / Chapter 1.1 --- 用聲音作爲輸出媒介 --- p.1 / Chapter 1.2 --- 各種聲音輸出方法 --- p.1 / Chapter 1.3 --- 音素合成法及VOTRAX SC01語音合成片 --- p.3 / Chapter 1.4 --- 國語輸出 --- p.3 / Chapter 第二章 --- 中文分折 / Chapter 2.1 --- 國語分析 --- p.4 / Chapter 2.1.1 --- 國語音素 --- p.4 / Chapter 2.1.1.1 --- 單元音 --- p.4 / Chapter 2.1.1.2 --- 輔音 --- p.5 / Chapter 2.1.2 --- 國語音素的互相結合 / Chapter 2.1.2.1 --- 複元音 --- p.6 / Chapter 2.1.2.2 --- 鼻元音 --- p.6 / Chapter 2.1.3 --- 國語音節 --- p.7 / Chapter 2.2 --- 漢詞 --- p.9 / Chapter 2.3 --- 漢字 --- p.9 / Chapter 第三章 --- 硬件和軟件的設計 / Chapter 3.1 --- 硬件設計 --- p.10 / Chapter 3.2 --- 軟件設計 --- p.11 / Chapter 3.2.1 --- 漢字編碼和音素地址表 --- p.12 / Chapter 3.2.2 --- 音素串表 --- p.13 / Chapter 3.2.3 --- 語音合成器操作程序 --- p.14 / Chapter 3.2.4 --- 語音合成器管理程序和音素編輯程序 --- p.15 / Chapter 第四章 --- 建立和發現 / Chapter 4.1 --- 硬件的建立 --- p.15 / Chapter 4.2 --- 軟件的建立 --- p.18 / Chapter 4.2.1 --- 表的建立 --- p.18 / Chapter 4.2.2 --- 程序的建立 --- p.23 / Chapter 第五章 --- 結論 --- p.24 / Chapter 附錄A --- 參考資料 --- p.26 / Chapter 附錄B --- 漢語輔音音素表 --- p.28 / Chapter 附錄C --- 漢語元音音素表 --- p.29 / Chapter 附錄D --- SC01音素表 --- p.31 / Chapter 附錄E --- 軟件應用 / Chapter E.1 --- 語音合成器操作程序應用 --- p.34 / Chapter E.2 --- 語音合成器管理程序應用 --- p.41 / Chapter E.3 --- 音素編輯程序應用 --- p.45 / Chapter 附錄F --- 中英名詞對照表 / Chapter F.1 --- 聲音及發聲方法 --- p.53 / Chapter "F,2" --- 硬件 --- p.53 / Chapter F.3 --- 軟件 --- p.53 / Chapter 附錄G --- 語音合成器硬件電路圖 --- p.55