The speech recognition based on the bark wavelet and CZCPA features

被引:0
|
作者
Zhang Xueying [1 ]
Bai Jing [1 ]
机构
[1] Taiyuan Univ Technol, Coll Informat Engn, Shanxi 030024, Peoples R China
关键词
Bark scale; speech recognition; wavelet; feature extraction;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The paper uses a new wavelet-Bark wavelet to meet critical frequency band division demand that is consistent with the perception of the human ear to the speech frequency. It is used in front-end processing of speech recognition system as filter bank instead of original FIR filter bank for improving the system performance. The paper gave the concept and parameter setting method of Bark wavelet. At the same time, the paper also presents an improved feature: CZCPA (Combining Zero-Crossings with Peak Amplitudes) based on ZCPA feature. The new feature includes the information of speech signals and its difference signal. It can improve system performance to some extent. The recognition network uses HMM. The experiment results show that the results of using CZCPA feature with Bark wavelet filters as front-end processor are superior to the results of using ZCPA feature with FIR filter as front-end in speech recognition system.
引用
收藏
页码:318 / +
页数:2
相关论文
共 50 条
  • [31] An improved wavelet-based speech enhancement by using speech signal features
    Ayat, Saeed
    Manzuri-Shalmani, M. T.
    Dianat, Roohollah
    COMPUTERS & ELECTRICAL ENGINEERING, 2006, 32 (06) : 411 - 425
  • [32] Wavelet Based Entropy Features for Facial Expression Recognition
    Mazumder, Badhan
    Nurullah, Md
    2020 IEEE REGION 10 SYMPOSIUM (TENSYMP) - TECHNOLOGY FOR IMPACTFUL SUSTAINABLE DEVELOPMENT, 2020, : 1347 - 1350
  • [33] Recognition of palmprints using wavelet-based features
    Kumar, A
    Shen, HC
    6TH WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL IX, PROCEEDINGS: IMAGE, ACOUSTIC, SPEECH AND SIGNAL PROCESSING II, 2002, : 515 - 518
  • [34] Seismic buffer recognition using wavelet based features
    Hoffman, AJ
    Hoogenboezem, C
    van der Merwe, NT
    Tollig, CJA
    IGARSS '98 - 1998 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, PROCEEDINGS VOLS 1-5: SENSING AND MANAGING THE ENVIRONMENT, 1998, : 1333 - 1335
  • [35] Speech Emotion Recognition Based on Wavelet Packet Coefficient Model
    Wang, Kunxia
    An, Ning
    Li, Lian
    2014 9TH INTERNATIONAL SYMPOSIUM ON CHINESE SPOKEN LANGUAGE PROCESSING (ISCSLP), 2014, : 478 - 482
  • [36] Speech Endpoint Recognition Algorithm Based on Wavelet Coefficient Variance
    Zheng, Gang
    2020 5TH INTERNATIONAL CONFERENCE ON SMART GRID AND ELECTRICAL AUTOMATION (ICSGEA 2020), 2020, : 226 - 230
  • [37] A Discrete Wavelet Transform Based Approach to Hindi Speech Recognition
    Ranjan, Shivesh
    2010 INTERNATIONAL CONFERENCE ON SIGNAL ACQUISITION AND PROCESSING: ICSAP 2010, PROCEEDINGS, 2010, : 345 - 348
  • [38] Speech Emotion Recognition Based on Entropy of Enhanced Wavelet Coefficients
    Sultana, S.
    Shahnaz, C.
    Fattah, S. A.
    Ahmmed, I.
    Zhu, W. -P.
    Ahmad, M. O.
    2014 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2014, : 137 - 140
  • [39] Speech Emotion Recognition Based on Wavelet Transform and Improved HMM
    Han Zhiyan
    Wang Jian
    2013 25TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2013, : 3156 - 3159
  • [40] WAVELET BASED CEPSTRAL COEFFICIENTS FOR NEURAL NETWORK SPEECH RECOGNITION
    Adam, T. B.
    Salam, M. S.
    Gunawan, T. S.
    2013 IEEE INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING APPLICATIONS (IEEE ICSIPA 2013), 2013, : 447 - 451