Complex cepstrum factorization for statistical parametric synthesis

This paper presents a study on complex cepstrum-based speech factorization for acoustic modeling in statistical parametric synthesizers. The factorization is conducted assuming that both vocal tract resonance and glottal flow effect are fully represented by the complex cepstrum. We investigated four different forms to represent the complex cepstrum in the acoustic models and compared their performances in terms of objective measures between reconstructed and natural waveforms and final quality of the synthesized speech. According to experimental results, the all-pass/minimum-phase and real cepstrum/phase cepstrum decompositions are the best ones in terms of preserving the complex cepstrum information after the parameter generation process.