Large vocabulary continuous speech recognition for cantonese.

• Other Authors: Wong, Yiu Wing.
• Format: Others
• Language: English; Chinese
• Published: 2000
• Subjects: Automatic speech recognition; Cantonese dialects > Data processing
• Online Access: http://library.cuhk.edu.hk/record=b5890466; http://repository.lib.cuhk.edu.hk/en/item/cuhk-323154

Wong Yiu Wing = 粤語的大詞彙、連續語音識別系統 / 黃耀榮. === Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. === Includes bibliographical references. === Text in English; abstracts in English and Chinese. === Wong Yiu Wing = Yue yu de da ci hui, lian xu yu yin shi bie xi tong / Huang Yaorong. === Chapter 1 --- Introduction --- p.1 === Chapter 1.1 --- Progress of Large Vocabulary Continuous Speech Recognition for Chinese --- p.2 === Chapter 1.2 --- Objectives of the Thesis --- p.5 === Chapter 1.3 --- Thesis Outline --- p.6 === Reference --- p.7 === Chapter 2 --- Fundamentals of Large Vocabulary Continuous Speech Recognition for Cantonese --- p.9 === Chapter 2.1 --- Characteristics of Cantonese --- p.9 === Chapter 2.1.1 --- Cantonese Phonology --- p.9 === Chapter 2.1.2 --- Written Cantonese versus Spoken Cantonese --- p.12 === Chapter 2.2 --- Techniques for Large Vocabulary Continuous Speech Recognition --- p.13 === Chapter 2.2.1 --- Feature Representation of the Speech Signal --- p.14 === Chapter 2.2.2 --- Hidden Markov Model for Acoustic Modeling --- p.15 === Chapter 2.2.3 --- Search Algorithm --- p.17 === Chapter 2.2.4 --- Statistical Language Modeling --- p.18 === Chapter 2.3 --- Discussions --- p.19 === Reference --- p.20 === Chapter 3 --- Acoustic Modeling for Cantonese --- p.21 === Chapter 3.1 --- The Speech Database --- p.21 === Chapter 3.2 --- Context-Dependent Acoustic Modeling --- p.22 === Chapter 3.2.1 --- Context-Independent Initial / Final Models --- p.23 === Chapter 3.2.2 --- Construction of Context-Dependent TrilF Models from Context- Independent IF Models --- p.26 === Chapter 3.2.3 --- Data Sharing in Acoustic Modeling --- p.27 === Chapter 1. --- Sparse Data Problem --- p.27 === Chapter 2. --- Decision-Tree Based State Clustering --- p.28 === Chapter 3.3 --- Experimental Results --- p.31 === Chapter 3.4 --- Error Analysis and Discussions --- p.33 === Chapter 3.4.1 --- Recognition Accuracy vs. Model Complexity --- p.33 === Chapter 3.4.2 --- Initial / Final Confusion Matrices --- p.34 === Chapter 3.4.3 --- Analysis of Phonetic Trees --- p.39 === Chapter 3.4.4 --- The NULL Initial HMM --- p.42 === Chapter 3.4.5 --- Comments on the CUSENT Speech Corpus --- p.42 === References --- p.44 === Chapter 4 --- Language Modeling for Cantonese --- p.46 === Chapter 4.1 --- N-gram Language Model --- p.46 === Chapter 4.1.1 --- Problems in Building an N-gram Language Model --- p.47 === Chapter 1. --- The Zero-Probability Problem and Backoff N-gram --- p.48 === Chapter 4.1.2 --- Perplexity of a Language Model --- p.49 === Chapter 4.2 --- N-gram Modeling in Cantonese --- p.50 === Chapter 4.2.1 --- The Vocabulary and Word Segmentation --- p.50 === Chapter 4.2.2 --- Evaluation of Chinese Language Models --- p.53 === Chapter 4.3 --- Character-Level versus Word-Level Language Models --- p.54 === Chapter 4.4 --- Language Modeling in a Specific Domain --- p.57 === Chapter 4.4.1 --- Language Model Adaptation to the Financial Domain --- p.57 === Chapter 1. --- Vocabulary Refinement --- p.57 === Chapter 2. --- The Seed Financial Bigram --- p.58 === Chapter 3. --- Linear Interpolation of Two Bigram models --- p.59 === Chapter 4. --- Performance of the Interpolated Language Model --- p.60 === Chapter 4.5 --- Error Analysis and Discussions --- p.61 === References --- p.63 === Chapter 5 --- Integration of Acoustic Model and Language Model --- p.65 === Chapter 5.1 --- One-Pass Search versus Multi-Pass Search --- p.66 === Chapter 5.2 --- A Two-Pass Decoder for Chinese LVCSR --- p.68 === Chapter 5.2.1 --- The First Pass Search --- p.69 === Chapter 5.2.2 --- The Second Pass Search --- p.72 === Chapter 5.3 --- Experimental Results --- p.73 === Chapter 5.4 --- Error Analysis and Discussions --- p.75 === Chapter 5.4.1 --- Vocabulary and Search --- p.75 === Chapter 5.4.2 --- Expansion of the Syllable Lattice --- p.76 === Chapter 5.4.3 --- Perplexity and Recognition Accuracy --- p.78 === Reference --- p.80 === Chapter 6 --- Conclusions and Suggestions for Future Work --- p.82 === Chapter 6.1 --- Conclusions --- p.82 === Chapter 6.2 --- Suggestions for future work --- p.84 === Chapter 1. --- Speaker Adaptation --- p.84 === Chapter 2. --- Tone Recognition --- p.84 === Reference --- p.85 === Appendix I Base Syllable Table --- p.86 === Appendix II Phonetic Question Set --- p.87