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Table of contents
1 Introduction
1.1 Motivation
1.2 The Aim of This Work
1.3 Possible Solution
1.4 Overview
2 Background
2.1 Automatic Speech Recognition
2.1.1 Acoustic Phonetic Approach
2.1.2 Pattern Recognition Approach
2.1.3 Artificial Intelligence Approach (Knowledge Based Approach)
2.2 Search by Voice Efforts at Google
2.3 Difficulties with Automatic Speech Recognition
2.3.1 Human
2.3.2 Technology
2.3.3 Language
2.4 Metrics
2.4.1 Word Error Rate
2.4.2 Quality
2.4.3 Out of Vocabulary Rate
2.4.4 Latency
2.5 Phonetic algorithm
2.5.1 Soundex
2.5.2 Daitch-Mokotoff Soundex System
2.5.3 Metaphone
2.5.4 Double Metaphone
2.5.5 Metaphone
2.5.6 Beider Morse Phonetic Matching
2.6 Google Glass
2.6.1 Google Glass Principles
2.6.2 User Interface
2.6.3 Technology Specs
2.6.4 Glass Development Kit
2.6.5 The Mirror API
2.7 Elastic-search
2.7.1 NGrams Tokenizer
2.7.2 Phonetic Filters
3 Related Works
4 Implementation
4.1 Motivation of selected Phonetic Algorithms
4.2 Motivation of Showing 6 Rows in Each Page
4.2.1 Google Glass Limitation
4.2.2 Users Behavior in Searching Areas
4.2.3 Conclusion
4.3 Data Set
4.4 Norconex
4.4.1 Importer Configuration Options
4.4.2 Committer Configuration Options
4.4.3 More Options
4.5 Elasticsearch
4.6 Demo Of Application
5 Evaluation
5.1 Test data
5.2 Quantity Tests
5.3 Result
5.4 Best Algorithm For Google Glass
5.4.1 Improving Precision and F-measure
5.5 Conclusion
6 Discussion and Conclusions
6.1 Development Limitations
6.2 Further Research
List of Tables
List of Figures
Bibliography
Appendices
