Title :
Speech analysis/synthesis by Gaussian mixture approximation of the speech spectrum for voice conversion
Author :
Amini, Jalal ; Shahrebabaki, Abdoreza Sabzi ; Shokouhi, Navid ; Sheikhzadeh, H. ; Raahemifar, Kaamran ; Eslami, Mohammad
Author_Institution :
Dept. of Electr. Eng., Amirkabir Univ. of Technol., Tehran, Iran
Abstract :
Voice conversion typically employs spectral features to convert a source voice to a target voice. In this paper, we propose a simple method of fitting the STRAIGHT spectrum with Gaussian mixture (GM) models for speech analysis/synthesis and spectral modification. The mean values of the Gaussians are pre-determined based on Mel-frequency spacing. The standard deviations are also adaptively adjusted using the constant-Q principle and the spectrum amplitudes. Finally, the weights of the Gaussians are determined by sampling the log-spectrum at Mel-frequencies. The proposed analysis/synthesis method (MFLS-GM) is employed for speech analysis/synthesis and voice conversion. Subjective evaluations employing MOS and ABX demonstrate superior performance of the voice conversion using the MFLS-GM compared to systems employing MFCC features. The computation cost of the proposed analysis/synthesis method is also much lower than those based on MFCC.
Keywords :
Gaussian processes; approximation theory; feature extraction; mixture models; spectral analysis; speech processing; speech synthesis; ABX; GM models; Gaussian mixture approximation; Gaussian mixture model; MFCC features; MFLS-GM; MOS; Mel-frequency spacing; constant-Q principle; spectral features; spectral modification; spectrum amplitudes; speech analysis-synthesis; speech spectrum; standard deviations; straight spectrum fitting; voice conversion; Lead; Mel frequency cepstral coefficient; Smoothing methods; Speech; Vectors; Analysis/Synthesis; Feature Extraction; GMM; STRAIGHT; Voice Conversion;
Conference_Titel :
Signal Processing and Information Technology(ISSPIT), 2013 IEEE International Symposium on
Conference_Location :
Athens
DOI :
10.1109/ISSPIT.2013.6781919