Speaker Identification Based on Incremental Learning Neural Network

Neural Network based Classification for Speaker Identification

Speaker Recognition is a challenging task and is widely used in many speech aided applications. This study proposes a new Neural Network (NN) model for identifying the speaker, based on the acoustic features of a given speech sample extracted by applying wavelet transform on raw signals. Wrapper based feature selection applies dimensionality reduction by kernel PCA and ranking by Info gain. Onl...

Wavelet Formants Speaker Identification Based System via Neural Network

In this paper Discrete wavelet Transform with logarithmic Power Spectrum Density (PSD) are combined for speaker formants extraction, to be used as evident classification features. For classification, Feed Forward Back Propagation Neural Network FFBNN method is proposed. The Discrete Wavelet formants Neural Network DWFNNT system works with excellent capability of features tracking even with 0dB ...

Two Novel Learning Algorithms for CMAC Neural Network Based on Changeable Learning Rate

Cerebellar Model Articulation Controller Neural Network is a computational model of cerebellum which acts as a lookup table. The advantages of CMAC are fast learning convergence, and capability of mapping nonlinear functions due to its local generalization of weight updating, single structure and easy processing. In the training phase, the disadvantage of some CMAC models is unstable phenomenon...

On Acceleration of Incremental Learning in Chaotic Neural Network

Analytical Incremental Learning: Fast Constructive Learning Method for Neural Network

13:20 13:40 Analytical Incremental Learning: Fast Constructive Learning Method for Neural Network Syukron Ishaq Alfarozi, Noor Akhmad Setiawan, Teguh Bharata Adji, Kuntpong Woraratpanya, Kitsuchart Pasupa, Masanori Sugimoto Faculty of Information Technology, King Mongkut’s Institute of Technology Ladkrabang Department of Electrical Engineering and Information Technology, Universitas Gadjah Mada...