Speech recognition of specific two-word Chinese vocabulary by applying Fourier transform twice to the broad-band spectrogram

Di Pan; Ying Wei; Shili Liang; Tingfa Xu; Shuangwei Wang

doi:10.1109/EIIS.2017.8298546

Speech recognition of specific two-word Chinese vocabulary by applying Fourier transform twice to the broad-band spectrogram

Di Pan, Ying Wei, Shili Liang, Tingfa Xu, Shuangwei Wang

School of Optics and Photonics

Northeast Normal University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper illustrates a method to recognize the speech of specific two-word Chinese vocabulary by analyzing speech signals using a broad-band spectrogram after Fourier transform is applied to it twice. First, we analyze the broad-band spectrogram in the frequency domain and its corresponding voice characteristics in detail after applying Fourier transform twice. Then, binary width zoning column projection is carried out in the broad-band spectrogram frequency domain. The projection value is treated as the characteristic value of speech recognition feature and the support vector machine (SVM) is considered as the classifier for recognizing the speech of specific two-word Chinese vocabulary. A total of 1000 voice samples were used in the simulation. The results using this method show a remarkable recognition rate of 93.4%. The proposed method provides a new way for vocabulary recognition.

Original language	English
Title of host publication	1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017
Editors	Jun-Bao Li
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781538608432
DOIs	https://doi.org/10.1109/EIIS.2017.8298546
Publication status	Published - 2 Jul 2017
Event	1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017 - Harbin, China Duration: 3 Jun 2017 → 5 Jun 2017

Publication series

Name	1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017
Volume	2018-January

Conference

Conference	1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017
Country/Territory	China
City	Harbin
Period	3/06/17 → 5/06/17

Keywords

Broad-band spectrogram
Fourier transform twice
Support vector machine (SVM)

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10.1109/EIIS.2017.8298546

Cite this

Pan, D., Wei, Y., Liang, S., Xu, T., & Wang, S. (2017). Speech recognition of specific two-word Chinese vocabulary by applying Fourier transform twice to the broad-band spectrogram. In J.-B. Li (Ed.), 1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017 (pp. 1-6). (1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EIIS.2017.8298546

Pan, Di ; Wei, Ying ; Liang, Shili et al. / Speech recognition of specific two-word Chinese vocabulary by applying Fourier transform twice to the broad-band spectrogram. 1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017. editor / Jun-Bao Li. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1-6 (1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017).

@inproceedings{70b1b52bad30434395de828a4dce08ec,

title = "Speech recognition of specific two-word Chinese vocabulary by applying Fourier transform twice to the broad-band spectrogram",

abstract = "This paper illustrates a method to recognize the speech of specific two-word Chinese vocabulary by analyzing speech signals using a broad-band spectrogram after Fourier transform is applied to it twice. First, we analyze the broad-band spectrogram in the frequency domain and its corresponding voice characteristics in detail after applying Fourier transform twice. Then, binary width zoning column projection is carried out in the broad-band spectrogram frequency domain. The projection value is treated as the characteristic value of speech recognition feature and the support vector machine (SVM) is considered as the classifier for recognizing the speech of specific two-word Chinese vocabulary. A total of 1000 voice samples were used in the simulation. The results using this method show a remarkable recognition rate of 93.4%. The proposed method provides a new way for vocabulary recognition.",

keywords = "Broad-band spectrogram, Fourier transform twice, Support vector machine (SVM)",

author = "Di Pan and Ying Wei and Shili Liang and Tingfa Xu and Shuangwei Wang",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017 ; Conference date: 03-06-2017 Through 05-06-2017",

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language = "English",

series = "1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017",

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Pan, D, Wei, Y, Liang, S, Xu, T & Wang, S 2017, Speech recognition of specific two-word Chinese vocabulary by applying Fourier transform twice to the broad-band spectrogram. in J-B Li (ed.), 1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017. 1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-6, 1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017, Harbin, China, 3/06/17. https://doi.org/10.1109/EIIS.2017.8298546

Speech recognition of specific two-word Chinese vocabulary by applying Fourier transform twice to the broad-band spectrogram. / Pan, Di; Wei, Ying; Liang, Shili et al.
1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017. ed. / Jun-Bao Li. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1-6 (1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Speech recognition of specific two-word Chinese vocabulary by applying Fourier transform twice to the broad-band spectrogram

AU - Pan, Di

AU - Wei, Ying

AU - Liang, Shili

AU - Xu, Tingfa

AU - Wang, Shuangwei

PY - 2017/7/2

Y1 - 2017/7/2

N2 - This paper illustrates a method to recognize the speech of specific two-word Chinese vocabulary by analyzing speech signals using a broad-band spectrogram after Fourier transform is applied to it twice. First, we analyze the broad-band spectrogram in the frequency domain and its corresponding voice characteristics in detail after applying Fourier transform twice. Then, binary width zoning column projection is carried out in the broad-band spectrogram frequency domain. The projection value is treated as the characteristic value of speech recognition feature and the support vector machine (SVM) is considered as the classifier for recognizing the speech of specific two-word Chinese vocabulary. A total of 1000 voice samples were used in the simulation. The results using this method show a remarkable recognition rate of 93.4%. The proposed method provides a new way for vocabulary recognition.

AB - This paper illustrates a method to recognize the speech of specific two-word Chinese vocabulary by analyzing speech signals using a broad-band spectrogram after Fourier transform is applied to it twice. First, we analyze the broad-band spectrogram in the frequency domain and its corresponding voice characteristics in detail after applying Fourier transform twice. Then, binary width zoning column projection is carried out in the broad-band spectrogram frequency domain. The projection value is treated as the characteristic value of speech recognition feature and the support vector machine (SVM) is considered as the classifier for recognizing the speech of specific two-word Chinese vocabulary. A total of 1000 voice samples were used in the simulation. The results using this method show a remarkable recognition rate of 93.4%. The proposed method provides a new way for vocabulary recognition.

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Pan D, Wei Y, Liang S, Xu T, Wang S. Speech recognition of specific two-word Chinese vocabulary by applying Fourier transform twice to the broad-band spectrogram. In Li JB, editor, 1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1-6. (1st International Conference on Electronics Instrumentation and Information Systems, EIIS 2017). doi: 10.1109/EIIS.2017.8298546

Speech recognition of specific two-word Chinese vocabulary by applying Fourier transform twice to the broad-band spectrogram

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