Estimating glottal source waveforms and vocal tract shapes is typically done by processing the speech signal using an inverse filter and then fitting the residual signal using the glottal source model. However, due to source-tract interactions, the estimation accuracy is reduced. In this paper, we propose a method to estimate glottal source waveforms and vocal tract shapes simultaneously based on an analysis-by-synthesis approach with a source-filter model constructed of an Auto-Regressive eXogenous (ARX) model and the Liljencrants-Fant (LF) model. Since the optimization of multiple parameters makes simultaneous estimation difficult, we first initialize the glottal source parameters using the inverse filter method, and then simultaneously estimate the accurate parameters of the glottal sources and the vocal tract shapes using an analysis-by-synthesis approach. Experimental results with synthetic and real speech signals showed that the proposed method has higher estimation accuracy than using the inverse filter.
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This study was supported by a Grant-in-Aid for Scientific Research (A) (No. 25240026), JST-Mirai Program (JP-MJMI18D1) and China Scholarship Council (CSC).
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Li, Y., Sakakibara, K. & Akagi, M. Simultaneous Estimation of Glottal Source Waveforms and Vocal Tract Shapes from Speech Signals Based on ARX-LF Model. J Sign Process Syst (2019). https://doi.org/10.1007/s11265-019-01510-4
- Glottal source waveform
- Vocal tract shape
- ARX-LF model