Earticle

초록

영어

In the area of speech signal processing, real background noise is important problem for noise reduction, therefore more skillful methods are required in this area. Accordingly, this paper proposes a spectrum recovery algorithm using a signal-to- noise ratio classification method based on a classification of a voiced or unvoiced signal. Therefore, the proposed algorithm recovers a speech spectrum from a noisy speech spectrum using a time-delay neural network for noise reduction. As such, the proposed system detects the voiced and unvoiced signal, then reduces the noise spectrums for each input frame using the time-delay neural network. Based on measuring correct classification rates and spectrum recovery results, experiments confirm that the proposed algorithm is effective for speech degraded by various noises.

목차

Abstract
 1. Introduction
 2. Noisy Speech Signal
 3. Proposed Time-Delay Neural Network (TDNN)
 4. Experimental Results
  4.1. Speech and Noise Database
  4.2. Classification Tests by Proposed TDNN System
  4.3. Experimental Results of Spectrum Recovery
 5. Conclusions
 References

키워드

저자

• Jae Seung Choi [ Department of Electronic Engineering, College of Engineering, Silla University, 140 Baegyang-daero (Blvd), 700 Beon-gil (Rd), Sasang-gu, Busan, 617-736, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605