Journal ArticleDOI
Voice Conversion Based on Weighted Frequency Warping
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TLDR
Compared to standard probabilistic systems, Weighted Frequency Warping results in a significant increase in quality scores, whereas the conversion scores remain almost unaltered.Abstract:
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.read more
Citations
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Journal ArticleDOI
Spoofing and countermeasures for speaker verification
TL;DR: A survey of past work and priority research directions for the future is provided, showing that future research should address the lack of standard datasets and the over-fitting of existing countermeasures to specific, known spoofing attacks.
Spoofing and countermeasures for speaker verification: a sur vey
TL;DR: In this paper, the authors provide a survey of spoofing countermeasures for automatic speaker verificati on, highlighting the need for more effort in the future to ensure adequate protection against spoofing attacks.
Journal ArticleDOI
Voice conversion using deep neural networks with layer-wise generative training
TL;DR: A DNN is used to construct a global non-linear mapping relationship between the spectral envelopes of two speakers to significantly improve the performance in terms of both similarity and naturalness compared to conventional methods.
Proceedings ArticleDOI
Voice conversion from non-parallel corpora using variational auto-encoder
TL;DR: In this article, a variational auto-encoder-decoder framework for spectral conversion with unaligned corpora is proposed. But it does not use parallel corpora or phonetic alignments to train a spectral conversion system.
Journal ArticleDOI
An overview of voice conversion systems
TL;DR: An overview of real-world applications of VC systems, extensively study existing systems proposed in the literature, and discuss remaining challenges are provided.
References
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Journal ArticleDOI
Statistical Parametric Speech Synthesis
TL;DR: This paper gives a general overview of techniques in statistical parametric speech synthesis, and contrasts these techniques with the more conventional unit selection technology that has dominated speech synthesis over the last ten years.
Journal ArticleDOI
Continuous probabilistic transform for voice conversion
TL;DR: The design of a new methodology for representing the relationship between two sets of spectral envelopes and the proposed transform greatly improves the quality and naturalness of the converted speech signals compared with previous proposed conversion methods.
Journal ArticleDOI
Voice Conversion Based on Maximum-Likelihood Estimation of Spectral Parameter Trajectory
TL;DR: In this article, a Gaussian mixture model (GMM) of the joint probability density of source and target features is employed for performing spectral conversion between speakers, and a conversion method based on the maximum-likelihood estimation of a spectral parameter trajectory is proposed.
Proceedings ArticleDOI
Low-delay voice conversion based on maximum likelihood estimation of spectral parameter trajectory.
TL;DR: The 9th Annual Conference of the International Speech Communication Association, September 22-26, 2008, Brisbane, Australia as discussed by the authors, was held at the University of Queensland, Queensland, Australia.
Proceedings ArticleDOI
Voice conversion through vector quantization
TL;DR: The authors propose a new voice conversion technique through vector quantization and spectrum mapping which makes it possible to precisely control voice individuality.