This research aims at using knowledge representation methods to simulate intra-sentence tone sandhi in Taiwanese. The simulation system includes a Taiwanese tone group parser and a simulation-monitoring interface that employs expert system techniques combined with linguistic knowledge and Taiwanese language experience to create a tone sandhi processing model. The significance of this study lies in three main aspects: first, it proposes the Tonal Derivation Strategy, which suggests that determining the tones of words within a sentence can also determine the boundaries of Taiwanese tone groups, and then verifies this through the implementation of the tone group parser. Second, it describes how to use default tone forms, default parts of speech (POS), and context mode marks to convert linguistic knowledge and experience into a knowledge base and illustrates the process of tone determination through the connection between the inference engine and the knowledge base. Finally, through the simulation monitoring procedure, debugging efficiency can be further optimized. Since Taiwanese tone sandhi is indeed closely related to the context, the simulation of Taiwanese tone sandhi is a relatively complex one-to-many mapping in AI application. The tone group parser is essentially an automatic tagging program for Taiwanese tone form that can be applied to Taiwanese language processing system.
Contents
1 Introduction
1.1 Statement of the Problem
1.2 Limitations of the Study
1.3 Significance of the Simulation of Taiwanese Tone Sandhi
2. Literature Review
2.1 The Nature of the Taiwanese Language: Phonological and Structural Perspectives
2.2 The Properties of Taiwanese Tone Sandhi and the Formation of Tone Groups
2.3 Rule-based Expert Systems
2.4 Knowledge Representation Methods and Examples of Linguistic Simulation
2.5 Deep Learning Methods and Modern Natural Language Processing
2.6 Current Research on Taiwanese Tone Sandhi and Text-to-speech System
3. The Development of Tonal Derivation Strategy
3.1 The Dilemma: Syntactic Analysis or Tone Form Analysis First?
3.2 Use of Medium Language
3.3 Tonal Derivation Strategy
3.4 From Tonal Derivation Strategy to Developing a Feasible Method
4. Methodology
4.1 Application of Knowledge Representation Method
4.2 Use Romanized Taiwanese as the written language
4.3 Frame-based Corpus
4.4 The Tagging of Markup Symbol and Rule Construction of Tone Sandhi Processor
4.5 The Configuration and Management of Program Memory
4.6 Capturing Tone Groups from Taiwanese Sentences
4.7 Designing a Tone Group Feedback Function
4.8 Monitoring Interface
5. Implementation of Taiwnese Tone Sandhi Simulation System
5.1 Coding Procedure
5.1.1 Overview of the Programming Workflow
5.1.2 Practical Coding Procedure
5.2 Construction of Tone Sandhi Processor
5.2.1 How to Build Tone Sandhi Rules
5.2.2 Rule Interference
5.2.3 Instantiation of the Rule Base
5.2.4 Boolean Verification
5.3 Recursive Feedback Mechanism of Tone Group
5.4 Monitor Interface for Processing Tracing and Debugging
5.5 Function of the Inference Engine
5.6 Application of Simulation Data
5.7 Output of the simulator
5.8 Evaluation of Tone Sandhi Accuracy Test
5.8.1 Testing Materials
5.8.2 Results of Tone Sandhi Accuracy Test
5.8.3 Connection Test of Tone Group Parser and Text-to-speech Software
5.9 Ultimate Solution to Tone Sandhi Error
6. Conclusions and Future Outlook
6.1 Conclusions
6.2 Future Outlook
References
If you have expertise in artificial intelligence and Romanized Taiwanese and are interested in this topic, please contact the author at poirotdavid@yahoo.com.tw to download the full-text PDF file for evaluation.
This website is sponsored
by VIKON Corp.
Copyright July 1996.
All rights reserved.
Last update : 2024-12-31
Any comments? mail to:
poirotdavid@yahoo.com.tw.
poirotdavid@yahoo.com.tw.