Voicing Classification Based on Speech Spectrum Multi-Scale Product

In this work, we present a new method for voicing detection in speech signals. Our approach is based on the spectral analysis of the speech multi-scale product. It consists of operating a Short Time Fourier Transform (STFT) on the speech multi-scale product. The multi-scale product consists of making the product of the speech wavelet transform coefficients at three successive dyadic scales. We localize all the spectral ray and then we define the groups of maxima positions sorted respecting some rules. Regarding the formed groups a voicing decision is made. We evaluate our approach on the Keele University database. The experimental results show the effectiveness of our method comparatively to the state-of-the-art algorithms. Besides, the proposed approach is robust for noisy speech.