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Deep Neural Network Based Speech Enhancement

  • Rashmirekha Ram
  • Mihir Narayan Mohanty
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 768)

Abstract

Enhancement of the speech signal is an essential task in the adverse environment. Several algorithms have been designed from several years to improve the quality. Mostly Neural Network and its variants are utilized for classification purpose. This paper exhibits the speech enhancement method based on the Deep Neural Network (DNN) to improve the quality and to increase the Signal-to-Noise Ratio of the speech signal. Different hidden layers are set to test the results. The audio features are extracted by using the short time Fourier transforms. The use of audio features improves the speech enhancement performance of DNN. Segmental Signal-to-Noise Ratio (SegSNR) and Perceptual Evaluation of Speech Quality (PESQ) are measured to test the results.

Keywords

Deep neural network Adaptive linear neuron Perceptual evaluation of speech quality Segmental signal-to-noise ratio Neural network Speech enhancement 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Electronics and Communication EngineeringSiksha ‘O’ Anusandhan UniversityBhubaneswarIndia

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