Retrieving Vocal-Tract Resonance And Anti-Resonance From High-Pitched Vowels Using A Rahmonic Subtraction Technique
Zhao Zhang, Kiyoshi Honda, Jianguo Wei
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SPS
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Vocal tract resonances give rise to core spectral information of speech signals. Linear prediction and cepstral methods are widely used for this purpose. However, both approaches are prone to fail as the fundamental frequency (F0) rises. In this study, a new cepstral method is developed combined with a refined rahmonic subtraction technique (RS-CEPS) to extract spectral envelopes excited by glottal noise sources. A vowel synthesis system based on 3D-printed solid vocal tract models is used to obtain reference transfer functions for accuracy verification. A series of stable vowels /a/ was synthesized for a wide F0 range. By analyzing the synthetic vowels, the results showed that the RS-CEPS yields accurate estimates of resonance-peak and anti-resonance frequencies in comparison to those from the conventional methods. The RS-CEPS is simple and stable, offering a potential for expanding speech analysis applications.