TBE 모델을 사용하는 HMM 기반 음성합성기 성능 향상을 위한 하모닉 선택에 기반한 MVF 예측 방법

Abstract

In the two-band excitation (TBE) model, maximum voiced frequency (MVF) is the most important feature of the excitation parameter because the synthetic speech quality depends on MVF. Thus, this paper proposes an enhanced MVF estimation scheme based on the peak picking method. In the proposed scheme, the local peak and the peak lobe are picked from the spectrum of a linear predictive residual signal. The normalized distance between neighboring peak lobes is calculated and utilized as a feature to estimate MVF. Experimental results of both objective and subjective tests show that the proposed scheme improves synthetic speech quality compared with that of the conventional one.