A Framework for Multilingual Text-Independent Speaker Identification System

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Provided by: Science Productions
Topic: Software
Format: PDF
In this paper, the authors evaluate the performance of Extreme Learning Machine (ELM) and Gaussian Mixture Model (GMM) in the context of text independent multi lingual speaker identification for recorded and synthesized speeches. The type and number of filters in the filter bank, number of samples in each frame of the speech signal and fusion of model scores play a vital role in speaker identification accuracy and are analyzed in this paper. Extreme Learning Machine (ELM) uses a single hidden layer feed forward neural network for multilingual speaker identification. The individual Gaussian components of GMM best represent speaker-dependent spectral shapes that are effective in speaker identity.
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