Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
권호 표지
DOI QR코드

DOI QR Code

Speech Spectrum Enhancement Combined with Frequency-weighted Spectrum Shaping Filter and Wiener Filter

주파수가중 스펙트럼성형필터와 위너필터를 결합한 음성 스펙트럼 강조

  • Received : 2016.06.29
  • Accepted : 2016.07.15
  • Published : 2016.10.31
Download PDF
⟨ Previous Next ⟩

Abstract

In the area of digital signal processing, it is necessary to improve the quality of the speech signal after removing the background noise which exists in a various real environments. The important thing to consider when removing the background noise acoustically is that to solve the problem, depending on the information of the human auditory mechanism is mainly the amplitude spectrum of the speech signal. This paper introduces the characteristics of a frequency-weighted spectrum shaping filter for the extraction of the amplitude spectrum of the speech signal with the primary purpose. Therefore, this paper proposes an algorithm using the methods of a Wiener filter and the frequency-weighted spectrum shaping filter according to the acoustic model, after extracted the amplitude spectral information in the noisy speech signal. The spectral distortion (SD) output of the proposed algorithm is experimentally improved more than 5.28 dB compared to a conventional method.

디지털신호처리 분야에서 다양한 환경에서 존재하는 배경잡음을 제거하여 음성신호의 품질을 개선시키는 것은 반드시 필요한 문제이다. 음향학적으로 배경잡음을 제거할 때 고려해야 할 중요한 점은 인간의 청각기전이 주로 음성의 진폭 스펙트럼의 정보에 의존하여 문제 해결을 하고 있다는 사실이다. 본 논문에서는 음성의 진폭 스펙트럼의 추출을 주요 목적으로 하는 주파수가중 스펙트럼성형필터의 특성을 도입한다. 따라서 본 논문에서는 배경잡음으로 중첩된 음성신호 성분 중에 이 진폭 스펙트럼 정보를 추출하여, 위너 필터법과 음향학적인 모델에 의한 주파수가중 스펙트럼성형필터를 사용한 알고리즘을 제안한다. 본 실험에서는 스펙트럼 왜곡률(SD)에 의하여 제안한 알고리즘의 출력 SD가 기존의 다른 방법과 비교하여 약 5.28 dB 이상 개선되었다.

Keywords

References

  1. X. Dang and T. Nakai, "Noise reduction using modified phase spectra and Wiener Filter," 2011 IEEE International Workshop on Machine Learning for Signal Processing, pp. 1-5, September 18-21, 2011.
  2. J. Freudenberger and S. Stenzel, "Blind Matched Filtering for Speech Recording in Uncorrelated Noise," International Workshop on Acoustic Signal Enhancement, pp. 1-4, September 4-6, 2012.
  3. M. Mathe, S. P. Nandyala and T. K. Kumar, "Speech enhancement using Kalman Filter for white, random and color noise," International Conference on Devices, Circuits and Systems (ICDCS), pp. 195-198, March 15-16, 2012.
  4. J. H. L. Hansen and S. Nandkumar, "Robust Estimation of Speech in Noisy Backgrounds Based on Aspects of the Auditory Process," The Journal of the Acoustical Society of America, vol. 97, no. 6, pp. 3833-3849, June 1995. https://doi.org/10.1121/1.413108
  5. M. F. R. Chowdhury, S. A. Selouani and D. O'Shaughnessy, "A highly non-stationary noise tracking and compensation algorithm, with applications to speech enhancement and on-line ASR," IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 4337-4340, March 25-30, 2012.
  6. J. S. Choi, "Speech Processing System Using a Noise Reduction Neural Network Based on FFT Spectrums," The Journal of Information and Communication Convergence Engineering, vol. 10, no. 2, pp. 162-167, June 2012. https://doi.org/10.6109/jicce.2012.10.2.162
  7. J. S. Choi, "Formant Enhancement Algorithm of Speech Using Auditory Filter," The Journal of Korean Institute of Information Technology, vol. 11, no. 7, pp. 173-178, July 2013.
  8. S. F. Boll, "Suppression of acoustic noise in speech using spectral subtraction," IEEE Trans. Acoust., Speech, Signal Processing, vol.27, no.2, pp. 113-120, April 1979. https://doi.org/10.1109/TASSP.1979.1163209
  9. J. S. Choi, "A Wiener Filter Algorithm of Noise Subtraction Based on Threshold Detection," The Journal of Korean Institute of Information Technology, vol. 13, no. 7, pp. 51-56, July 2015. https://doi.org/10.14801/jkiit.2015.13.7.51
  10. J. S. Choi, "Noise Reduction Algorithm in Speech by Wiener Filter," The Journal of Korea Institute of Electronic Communication Sciences, vol. 8, no. 8, pp. 1293-1298, Sep. 2013. https://doi.org/10.13067/JKIECS.2013.8.9.1293
  11. N. Upadhyay, "An Improved Multi-band Speech Enhancement Utilizing Masking Properties of Human Hearing System," Fifth International Symposium on Electronic System Design, pp. 150-155, Dec. 15-17, 2014.
  12. Md. T. Islam, C. Shahnaz and S. A. Fattah, "Speech enhancement based on a modified spectral subtraction method," IEEE 57th International Midwest Symposium on Circuits and Systems, pp. 1085-1088, Aug. 3-6, 2014.
  13. S. Alaya, N. Zoghlami and Z. Lachiri, "Adaptive filter for perceptual speech enhancement," 12th International Multi-Conference on Systems, Signals & Devices, pp. 1-6, March 16-19, 2015.