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Synthetic speech is speech signals generated by text-to-speech (TTS) and voice conversion (VC) techniques. They impose a threat to speaker verification (SV) systems as an attacker may make use of TTS or VC to synthesize a speakers voice to cheat the SV system. To address this challenge, we study the detection of synthetic speech using long term magnitude and phase information of speech. As most of...
We propose a nonparametric framework for voice conversion, that is, exemplar-based sparse representation with residual compensation. In this framework, a spectrogram is reconstructed as a weighted linear combination of speech segments, called exemplars, which span multiple consecutive frames. The linear combination weights are constrained to be sparse to avoid over-smoothing, and high-resolution spectra...
The conventional statistical-based transformation functions for voice conversion have been shown to suffer over-smoothing and over-fitting problems. The over-smoothing problem arises because of the statistical average during estimating the model parameters for the transformation function. In addition, the large number of parameters in the statistical model cannot be well estimated from the limited...
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