Research on speech enhancement based on spectral subtraction and neural network
DOI:
CSTR:
Author:
Affiliation:

College of Physical Science and Technology, Central China Normal University, Wuhan 430079, China

Clc Number:

TN911.23

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Background noise is one of the noise sources of communication system, speech enhancement can reduce or eliminate noise interference, and improve speech intelligibility. Speech power spectrum is adopted orthogonal multi window spectrum estimation for smoothing processing, to reduce music noise from spectrum subtraction under the complicated noise environment. The loss of information and estimation have effectively reduced. Using adaptive spectral subtraction coefficient to adjust spectrum gain and floor to control the residual noise, using the optimized IMCRA algorithm for noise update to speech and silence, the enhanced speech signal has acquired by spectral subtraction and waveform reconstruction after the deep neural network trained data. The simulation results show that the noise reduction effect of speech is good, speech intelligibility is well.

    Reference
    Related
    Cited by
Get Citation
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:
  • Revised:
  • Adopted:
  • Online: August 15,2017
  • Published:
Article QR Code