Voice conversion algorithm based on Gaussian mixture model with dynamic frequency warping of straight spectrum

被引:0
|
作者
Toda, T [1 ]
Saruwatari, H [1 ]
Shikano, K [1 ]
机构
[1] Nara Inst Sci & Technol, Grad Sch Informat Sci, Ikoma, Nara 6300101, Japan
来源
2001 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I-VI, PROCEEDINGS: VOL I: SPEECH PROCESSING 1; VOL II: SPEECH PROCESSING 2 IND TECHNOL TRACK DESIGN & IMPLEMENTATION OF SIGNAL PROCESSING SYSTEMS NEURALNETWORKS FOR SIGNAL PROCESSING; VOL III: IMAGE & MULTIDIMENSIONAL SIGNAL PROCESSING MULTIMEDIA SIGNAL PROCESSING | 2001年
关键词
D O I
暂无
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
In the voice conversion algorithm based on the Gaussian Mixture Model (GMM) applied to STRAIGHT, quality of converted speech is degraded because the converted spectrum is exceedingly smoothed. In this paper, we propose the GMM-based algorithm with dynamic frequency warping to avoid the over-smoothing. We also propose an addition of the weighted residual spectrum, which is the difference between the GMM-based converted spectrum and the frequency-warped spectrum, to avoid the deterioration of conversion-accuracy on speaker individuality. Results of the evaluation experiments clarify that the converted speech quality is better than that of the GMM-based algorithm, and the conversion-accuracy on speaker individuality is the same as that of the GMM-based algorithm in the proposed method with the properly-weighted residual spectrum.
引用
收藏
页码:841 / 844
页数:4
相关论文
共 50 条
  • [11] Voice conversion using canonical correlation analysis based on Gaussian mixture model
    Jian, ZhiHua
    Yang, Zhen
    SNPD 2007: EIGHTH ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCE, NETWORKING, AND PARALLEL/DISTRIBUTED COMPUTING, VOL 1, PROCEEDINGS, 2007, : 210 - +
  • [12] Voice Conversion based on Continuous Frequency Warping and Magnitude Scaling
    Ye, Yuhang
    Lawlor, Bob
    2017 28TH IRISH SIGNALS AND SYSTEMS CONFERENCE (ISSC), 2017,
  • [13] An Exemplar-Based Approach to Frequency Warping for Voice Conversion
    Tian, Xiaohai
    Lee, Siu Wa
    Wu, Zhizheng
    Chng, Eng Siong
    Li, Haizhou
    IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2017, 25 (10) : 1863 - 1876
  • [14] Contribution on Gaussian Mixture Model Order Determination for Voice Conversion
    Ben Amara, Ahmed
    Ben Jebara, Sofia
    9TH INTERNATIONAL SYMPOSIUM ON SIGNAL, IMAGE, VIDEO AND COMMUNICATIONS (ISIVC 2018), 2018, : 87 - 92
  • [15] Robust voice activity detection algorithm based on complex Gaussian mixture model
    Lei, Jian-Jun
    Yang, Zhen
    Liu, Gang
    Guo, Jun
    Tianjin Daxue Xuebao (Ziran Kexue yu Gongcheng Jishu Ban)/Journal of Tianjin University Science and Technology, 2009, 42 (04): : 353 - 356
  • [16] A Voice Conversion System Based on the Harmonic plus Noise Excitation and Gaussian Mixture Model
    Wu Lifang
    Zhang Linghua
    PROCEEDINGS OF THE 2012 SECOND INTERNATIONAL CONFERENCE ON INSTRUMENTATION & MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC 2012), 2012, : 1575 - 1578
  • [17] Speech Analysis/Synthesis by Gaussian Mixture Approximation of the Speech Spectrum for Voice Conversion
    Amini, Jamal
    Shahrebabaki, Abdoreza Sabzi
    Shokouhi, Navid
    Sheikhzadeh, Hamid
    Raahemifa, Kaamran
    Eslami, Mehdi
    2013 IEEE INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY (IEEE ISSPIT 2013), 2013, : 428 - 433
  • [18] Voice conversion algorithm based on piecewise linear conversion rules of formant frequency and spectrum tilt
    NTT Human Interface Lab, Kanagawa, Japan
    Speech Commun, 2 (153-164):
  • [19] Bilingual Voice Conversion by Weighted Frequency Warping Based on Formant Space
    Yun, Young-Sun
    Ladner, Richard E.
    TEXT, SPEECH, AND DIALOGUE, TSD 2013, 2013, 8082 : 137 - 144
  • [20] Voice conversion using structured Gaussian mixture model in eigen space
    Li, Yangchun
    Yu, Yibiao
    Shengxue Xuebao/Acta Acustica, 2015, 40 (01): : 12 - 19