JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Speech Recognition for the Korean Vowel 'ㅣ' based on Waveform-feature Extraction and Neural-network Learning
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Speech Recognition for the Korean Vowel 'ㅣ' based on Waveform-feature Extraction and Neural-network Learning
Rho, Wonbin; Lee, Jongwoo; Lee, Jaewon;
 
 Abstract
With the recent increase of the interest in IoT in almost all areas of industry, computing technologies have been increasingly applied in human environments such as houses, buildings, cars, and streets; in these IoT environments, speech recognition is being widely accepted as a means of HCI. The existing server-based speech recognition techniques are typically fast and show quite high recognition rates; however, an internet connection is necessary, and complicated server computing is required because a voice is recognized by units of words that are stored in server databases. This paper, as a successive research results of speech recognition algorithms for the Korean phonemic vowel 'ㅏ', 'ㅓ', suggests an implementation of speech recognition algorithms for the Korean phonemic vowel 'ㅣ'. We observed that almost all of the vocal waveform patterns for 'ㅣ' are unique and different when compared with the patterns of the 'ㅏ' and 'ㅓ' waveforms. In this paper we propose specific waveform patterns for the Korean vowel 'ㅣ' and the corresponding recognition algorithms. We also presents experiment results showing that, by adding neural-network learning to our algorithm, the voice recognition success rate for the vowel 'ㅣ' can be increased. As a result we observed that 90% or more of the vocal expressions of the vowel 'ㅣ' can be successfully recognized when our algorithms are used.
 Keywords
Speech recognition;Vowel;Waveform feature;'ㅣ';Neural network;
 Language
Korean
 Cited by
 References
1.
Y. K. Lee, "Speech Interface Technology and Service Trend under the Smart Phone Environment," Information & Communications Magazine, Vol. 29, No. 4, pp. 3-9, 2012. (in Korean)

2.
H. S. Baek, S. H. Cho, D. S. Yook, "Connected Korean Digit Speech Recognition Using Syllable-based Recognition Units," Proc. of the KMMS Conference 2010, pp. 514-515, 2010. (in Korean)

3.
H. Jung, "Korean Speech Recognition Using Neural Networks," Korean Institute of Information Scientists and Engineers, pp. 63-82, 1993.

4.
D. K. Kim, C. G. Jeong, and H. Jeong, "Hierarchy and Modulatity in Time-Delay Neural Networks for Korean Phoneme Recognition using HMM," IEEK, Vol. 16, No. 1, pp. 81-84, 1994.

5.
T. W. Jang, H. Y. Kim, B. M. Kim, C. H, "Implementation of Real-time Vowel Recognition Mouse based on Smartphone," KIISE Transactions on Computing Practices, Vol. 21, No. 8, pp. 531-536, 2015. crossref(new window)

6.
J. H. Lee, J. W. Lee, J. W. Lee, "Korean Phonemes 'ㅅ', 'ㅈ', 'ㅊ' Recognition based on Sign Distribution Volatility," Communications of the Korean Institute of Information Scientists and Engineers, Vol. 19, pp. 377-382, 2013. (in Korean)

7.
J. W. Lee, "Speech Recognition of Korean Phonemes 'ㅅ', 'ㅈ', 'ㅊ' based on Volatility and Turning Points," KIISE Transactions on Computing Practices, Vol. 20, No. 11, pp. 579-585, 2014. crossref(new window)

8.
W. B. Roh, J. W. Lee, "Implementation of Korean Vowel 'ㅏ' Recognition based on Common Feature Extraction of Waveform Sequence," KIISE Transactions on Computing Practices, Vol. 20, No. 11, pp. 567- 572, 2014. crossref(new window)

9.
W. B. Rho, J. W. Lee, "Implementation of Waveform Sequence Feature Extraction For Korean Vowel 'ㅓ' Recognition," KCC2015, pp. 128-130, 2015 (in Korean)