Jamal Amini, Abdoreza Sabzi Shahrebabaki, Navid Shokouhi, H. Sheikhzadeh, K. Raahemifar, M. Eslami
{"title":"语音分析/合成的高斯混合近似的语音频谱的语音转换","authors":"Jamal Amini, Abdoreza Sabzi Shahrebabaki, Navid Shokouhi, H. Sheikhzadeh, K. Raahemifar, M. Eslami","doi":"10.1109/ISSPIT.2013.6781919","DOIUrl":null,"url":null,"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.","PeriodicalId":88960,"journal":{"name":"Proceedings of the ... IEEE International Symposium on Signal Processing and Information Technology. IEEE International Symposium on Signal Processing and Information Technology","volume":"12 1","pages":"000428-000433"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Speech analysis/synthesis by Gaussian mixture approximation of the speech spectrum for voice conversion\",\"authors\":\"Jamal Amini, Abdoreza Sabzi Shahrebabaki, Navid Shokouhi, H. Sheikhzadeh, K. Raahemifar, M. Eslami\",\"doi\":\"10.1109/ISSPIT.2013.6781919\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":88960,\"journal\":{\"name\":\"Proceedings of the ... IEEE International Symposium on Signal Processing and Information Technology. IEEE International Symposium on Signal Processing and Information Technology\",\"volume\":\"12 1\",\"pages\":\"000428-000433\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ... IEEE International Symposium on Signal Processing and Information Technology. IEEE International Symposium on Signal Processing and Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSPIT.2013.6781919\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... IEEE International Symposium on Signal Processing and Information Technology. IEEE International Symposium on Signal Processing and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPIT.2013.6781919","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Speech analysis/synthesis by Gaussian mixture approximation of the speech spectrum for voice conversion
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.