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Developments of Machine Learning Schemes for Dynamic Time-Wrapping-Based Speech Recognition
Joint Authors
Ding, Ing-Jr
Yen, Chih-Ta
Hsu, Yen-Ming
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-11-28
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
This paper presents a machine learning scheme for dynamic time-wrapping-based (DTW) speech recognition.
Two categories of learning strategies, supervised and unsupervised, were developed for DTW.
Two supervised learning methods, incremental learning and priority-rejection learning, were proposed in this study.
The incremental learning method is conceptually simple but still suffers from a large database of keywords for matching the testing template.
The priority-rejection learning method can effectively reduce the matching time with a slight decrease in recognition accuracy.
Regarding the unsupervised learning category, an automatic learning approach, called “most-matching learning,” which is based on priority-rejection learning, was developed in this study.
Most-matching learning can be used to intelligently choose the appropriate utterances for system learning.
The effectiveness and efficiency of all three proposed machine-learning approaches for DTW were demonstrated using keyword speech recognition experiments.
American Psychological Association (APA)
Ding, Ing-Jr& Yen, Chih-Ta& Hsu, Yen-Ming. 2013. Developments of Machine Learning Schemes for Dynamic Time-Wrapping-Based Speech Recognition. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-1031969
Modern Language Association (MLA)
Ding, Ing-Jr…[et al.]. Developments of Machine Learning Schemes for Dynamic Time-Wrapping-Based Speech Recognition. Mathematical Problems in Engineering No. 2013 (2013), pp.1-10.
https://search.emarefa.net/detail/BIM-1031969
American Medical Association (AMA)
Ding, Ing-Jr& Yen, Chih-Ta& Hsu, Yen-Ming. Developments of Machine Learning Schemes for Dynamic Time-Wrapping-Based Speech Recognition. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-1031969
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1031969