Voice transformation using PSOLA technique
Speech Communication - Eurospeech '91
Transformation of formants for voice conversion using artificial neural networks
Speech Communication - Special issue: voice conversion: state of the art and perspectives
Speaker transformation algorithm using segmental codebooks (STASC)
Speech Communication
Voice Characteristics Conversion for HMM-based Speech Synthesis System
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 3 - Volume 3
High-resolution voice transformation
High-resolution voice transformation
Speech synthesis using HMMs with dynamic features
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02
Review: Statistical parametric speech synthesis
Speech Communication
IEEE Transactions on Audio, Speech, and Language Processing
Quality-enhanced voice morphing using maximum likelihood transformations
IEEE Transactions on Audio, Speech, and Language Processing
Voice Conversion Based on Maximum-Likelihood Estimation of Spectral Parameter Trajectory
IEEE Transactions on Audio, Speech, and Language Processing
Voice conversion using linear prediction coefficients and artificial neural network
Proceedings of the CUBE International Information Technology Conference
Computer Speech and Language
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Any modification applied to speech signals has an impact on their perceptual quality. In particular, voice conversion to modify a source voice so that it is perceived as a specific target voice involves prosodic and spectral transformations that produce significant quality degradation. Choosing among the current voice conversion methods represents a trade-off between the similarity of the converted voice to the target voice and the quality of the resulting converted speech, both rated by listeners. This paper presents a new voice conversion method termed Weighted Frequency Warping that has a good balance between similarity and quality. This method uses a time-varying piecewise-linear frequency warping function and an energy correction filter, and it combines typical probabilistic techniques and frequency warping transformations. Compared to standard probabilistic systems, Weighted Frequency Warping results in a significant increase in quality scores, whereas the conversion scores remain almost unaltered. This paper carefully discusses the theoretical aspects of the method and the details of its implementation, and the results of an international evaluation of the new system are also included.