Wideband Parametric Speech Synthesis Using Warped Linear Prediction
نویسندگان
چکیده
This paper studies the use of warped linear prediction (WLP) for wideband parametric speech synthesis. As the sampling frequency is increased from the usual 16 kHz, linear frequency resolution of conventional linear prediction (LP) cannot efficiently model the speech spectrum. By using frequency warping that weights perceptually the most important formant information, spectral models with better accuracy and lower model orders can be utilized. In this work, WLP is embedded in a parametric speech synthesizer to efficiently create wideband synthetic speech. Experiments show that WLP-based wideband synthetic speech is rated better compared to narrowband speech and wideband LP-based speech.
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