JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2017, Vol. 52 ›› Issue (11): 29-36.doi: 10.6040/j.issn.1671-9352.0.2017.253

Previous Articles     Next Articles

Speech recognition of Russian short instructions based on DTW

WANG Tong, MA Yan-zhou, YI Mian-zhu*   

  1. Language Engineering Department, PLA University of Foreign Languages, Luoyang 471000, Henan, China
  • Received:2017-05-20 Online:2017-11-20 Published:2017-11-17

PDF (PC)

398

Abstract: Focus on speech recognition task with limited training corpus, this paper makes research of Russian speech recognition based on DTW(dynamic time warping)algorithm. Firstly, we study methods for combining speech recognition and machine translation with the speech corpus which annotating tags of cross language text. Secondly, based on the characteristics of Russian speech, in order to detected syllable endpoint, we set dynamic threshold according to the central vowel, which increased the speed by 34.4% and increased the accuracy by 14%. Finally, we extract the parameters of the static and dynamic characteristics by analyzing speech features of time domain and frequency domain. In addition, the DTW algorithm is improved to overcome the ill condition and reduce the computation scale with global restrictions and early discard strategies, which increased the speed by 4.8% and increased the accuracy by 19.7%. Experiments on the Russian short instruction set with 5 fold cross validation, and the accuracy of speech recognition reached 74.9%.

Key words: Russian speech recognition, endpoint detection, DTW algorithm, cross language speech recognition

CLC Number: 

  • TP391
[1] 张雪英.数字语音处理及Matlab仿真[M]. 北京:电子工业出版社,2016. ZHANG Xueying. Processing of digital speech and Matlab simulation[M]. Beijing: Electronics Industry Press, 2016.
[2] 韩纪庆,张磊,郑铁然,等.语音信号处理[M]. 北京:清华大学出版社,2013. HAN Jiqing, ZHANG Lei, ZHENG Tieran, et al. Processing of speech signal[M]. Beijing:Tsinghua University Press, 2013.
[3] 于俊婷,刘伍颖,易绵竹,等.国内语音识别研究综述[J]. 计算机光盘软件与应用,2014(10):76-78. YU Junting, LIU Wuying, YI Mianzhu, et al. Review of speech recognition in China[M].Computer CD Software and Applications, 2014(10):76-78.
[4] 徐来娣.俄语音节理论研究与俄语音节切分优化方案[J]. 中国俄语教学,2009, 28(4):69-72. XU Laidi. Russian syllable theory study andoptimization of Russian syllable segmentation[J]. Teaching Russian in China, 2009, 28(4):69-72.
[5] 徐来娣.俄汉语流重音声学实验对比研究[J]. 中国俄语教学,2016, 35(2):75-81. XU Laidi. A contrastive study of Russian and Chinese acoustics stream stress[J]. Teaching Russian In China, 2016, 35(2):75-81.
[6] 赵芳丽.中国人说俄语声学特征的实验分析及训练对策[J]. 中国俄语教学,2011, 30(3):76-79. ZHAO Fangli. Experimental analysis and training strategies of Russian acoustic features by Chinese[J]. Teaching Russian In China, 2011, 30(3):76-79.
[7] ZHAO Fangli. Russian pronunciation analysis utilized praat software[J]. Computer Engineering and Applications, 2012, 48(11):133-136.
[8] 马延周.基于标注新闻语料的俄语连续语音识别研究[D]. 郑州:解放军外国语学院, 2015. MAYanzhou. A study of Russian continuous speech recognition based on tagged news corpus[D]. Zhengzhou: PLA University of Foreign Language, 2015.
[9] 胡航.语音信号处理[M]. 哈尔滨:哈尔滨工业大学出版社,2009. HU Hang. Processing of speech signal[M]. Harbin: Harbin Institute of Technology Press, 2009.
[10] YOO IC,YOOK D. Robust voice activity detection using the spectral peaks of vowel sounds[J]. ETRI Journal, 2009, 31(4):451-453.
[11] ORTIZ P D, VILLA LF, SALAZAR C, et al. A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies[J]. Journal of Physics: Conference Series, 2016, 705(1):012037.
[12] 宋知用.MATLAB在语音信号分析与合成中的应用[M]. 北京:北京航空航天大学出版社,2013. SONG Zhiyong. MATLAB application in speech signal analysis and synthesis[M]. Beijing: Beihang University Press, 2013.
[13] SAKOE H, CHIBA S. Dynamic programming algorithm optimization for spoken word recognition[J]. IEEE Transactions on Acoustics, Speech and Signal Process, 1978, 26(1):43-49.
[14] 孙宏伟.基于DTW距离的时间序列相似性查询和shapelets分类算法研究[D]. 太原:太原理工大学,2016. SUN Hongwei. Research of time series distance similarity and shapelets classification algorithm based on DTW[D]. Taiyuan: Taiyuan University of Technology, 2016.
[1] GONG Shuang-shuang, CHEN Yu-feng, XU Jin-an, ZHANG Yu-jie. Extraction of Chinese multiword expressions based on Web text [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2018, 53(9): 40-48.
[2] YU Chuan-ming, ZUO Yu-heng, GUO Ya-jing, AN Lu. Dynamic discovery of authors research interest based on the combined topic evolutional model [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2018, 53(9): 23-34.
[3] . Reader emotion classification with news and comments [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2018, 53(9): 35-39.
[4] . Design and implementation of topic detection in Russian news based on ontology [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2018, 53(9): 49-54.
[5] LIAO Xiang-wen, ZHANG Ling-ying, WEI Jing-jing, GUI Lin, CHENG Xue-qi, CHEN Guo-long. User influence analysis of social media with temporal characteristics [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2018, 53(3): 1-12.
[6] YU Chuan-ming, FENG Bo-lin, TIAN Xin, AN Lu. Deep representative learning based sentiment analysis in the cross-lingual environment [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2018, 53(3): 13-23.
[7] ZHANG Jun, LI Jing-fei, ZHANG Rui, RUAN Xing-mao, ZHANG Shuo. Community detection algorithm based on effective resistance of network [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2018, 53(3): 24-29.
[8] PANG Bo, LIU Yuan-chao. Fusion of pointwise and deep learning methods for passage ranking [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2018, 53(3): 30-35.
[9] CHEN Xin, XUE Yun, LU Xin, LI Wan-li, ZHAO Hong-ya, HU Xiao-hui. Text feature extraction method for sentiment analysis based on order-preserving submatrix and frequent sequential pattern mining [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2018, 53(3): 36-45.
[10] ZHANG Xiao-dong, DONG Wei-guang, TANG Min-an, GUO Jun-feng, LIANG Jin-ping. gOMP reconstruction algorithm based on generalized Jaccard coefficient for compressed sensing [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2017, 52(11): 23-28.
[11] SUN Jian-dong, GU Xiu-sen, LI Yan, XU Wei-ran. Chinese entity relation extraction algorithms based on COAE2016 datasets [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2017, 52(9): 7-12.
[12] WANG Kai, HONG Yu, QIU Ying-ying, WANG Jian, YAO Jian-min, ZHOU Guo-dong. Study on boundary detection of users query intents [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2017, 52(9): 13-18.
[13] ZHANG Fan, LUO Cheng, LIU Yi-qun, ZHANG Min, MA Shao-ping. User preference prediction in heterogeneous search environment [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2017, 52(9): 26-34.
[14] YANG Yan, XU Bing, YANG Mu-yun, ZHAO Jing-jing. An emotional classification method based on joint deep learning model [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2017, 52(9): 19-25.
[15] YUAN Wei, YI Mian-zhu. Building a Russian-Chinese comparable corpus based on Wikipedia and its comparability calculation [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2017, 52(9): 1-6.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright 2018 © Editorial office of JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE)
Supported by Beijing Magtech Co.Ltd