Zhaoting Liu, Xiaodong Zhuang, Nikos Mastorakis, "Speech Segmentation Based on the Computation of Local Signal Manifold Dimension," WSEAS Transactions on Systems, vol. 22, pp. 416-422, 2023, DOI:10.37394/23202.2023.22.44
Zhaoting Liu, Xiaodong Zhuang, Nikos Mastorakis. Speech Segmentation Based on the Computation of Local Signal Manifold Dimension.
WSEAS Transactions on Systems. 2023;22:416-422. 10.37394/23202.2023.22.44
WSEAS Transactions on Systems
Print ISSN: 1109-2777, E-ISSN: 2224-2678
Volume 22, 2023
Speech Segmentation Based on the Computation of Local Signal Manifold Dimension
Authors: , ,
Abstract: A new computational method of unvoiced and voiced speech segmentation is proposed from the
perspective of local linear manifold analysis of speech signals. It is based on the estimation of the dimension of
short-time linear subspace. The subspace dimensional characteristics of the single phoneme signal are studied.
The local signal vector set is analyzed by using the PCA algorithm to estimate the dimension of the data matrix
formed by framing. The local PCA is used to analyze the speech signal to achieve the segmentation of unvoiced
and voiced pronunciation. Simulation experiments prove the effectiveness of the proposed method.
Pages: 416-422 WSEAS Transactions on Systems, ISSN / E-ISSN: 1109-2777 / 2224-2678, Volume 22, 2023, Art. #44 DOI: 10.37394/23202.2023.22.44
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