Comparative study of voice conversion framework with line spectral frequency and Mel-Frequency Cepstral Coefficients as features using artficial neural networks
暂无分享,去创建一个
[1] Kishore Prahallad,et al. Voice conversion using Artificial Neural Networks , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.
[2] Alexander Kain,et al. Design and evaluation of a voice conversion algorithm based on spectral envelope mapping and residual prediction , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).
[3] A. F. Machado,et al. VOICE CONVERSION: A CRITICAL SURVEY , 2010 .
[4] Hermann Ney,et al. A study on residual prediction techniques for voice conversion , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..
[5] Levent M. Arslan,et al. Subband based voice conversion , 2002, INTERSPEECH.
[6] K SREENIVASA RAO,et al. Role of neural network models for developing speech systems , 2011 .
[7] Mukesh A. Zaveri,et al. Complex Cepstrum Based Voice Conversion Using Radial Basis Function , 2014 .
[8] Alan W. Black,et al. The CMU Arctic speech databases , 2004, SSW.
[9] Levent M. Arslan,et al. Voice conversion by codebook mapping of line spectral frequencies and excitation spectrum , 1997, EUROSPEECH.
[10] Jagannath H. Nirmal,et al. Voice conversion using General Regression Neural Network , 2014, Appl. Soft Comput..
[11] V. Tiwari. MFCC and its applications in speaker recognition , 2010 .
[12] L. H. Zhang,et al. A ANN Based High Quality Method for Voice Conversion , 2010, 2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM).
[13] Kishore Prahallad,et al. Spectral Mapping Using Artificial Neural Networks for Voice Conversion , 2010, IEEE Transactions on Audio, Speech, and Language Processing.