JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Multi frequency band noise suppression system using signal-to-noise ratio estimation
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Multi frequency band noise suppression system using signal-to-noise ratio estimation
Oh, In Kyu; Lee, In Sung;
  PDF(new window)
 Abstract
This paper proposes a noise suppression method through SNR (Singal-to Noise Ratio) estimation in the two microphone array environment of close spacing. The conventional method uses a noise suppression method for a gain function obtained through the SNR estimation based on coherence function from full band. However, this method cause performance decreased by the noise damage that affects all the feature vector component. So, we propose a noise suppression method that allocates a frequency domain signal into N constant multi frequency band and each frequency band gets a gain function through SNR estimation based on coherence function. Performance evaluation of the proposed method is shown by comparison with PESQ (Perceptual Evaluation of Speech Quality) value which is an objective quality evaluation method provided by the ITU-T (International Telecommunications Union Telecommunication).
 Keywords
PSD (Power Spectrum Density);CSD (Cross-power Spectrum Density);Coherence function;Multi-band;
 Language
Korean
 Cited by
 References
1.
Z. I. Skordilis, A. Tsiami, P. P. Maragos, G. Potamianos, L. Spelgattil, and R. Sannino, "Multichannel speech enhancement using MEMS microphones," in IEEE ICASSP, 2729-2733 (2015).

2.
M. Kalamani, S. Valarmathy, and M. Krishnamoorthi, "Noise tracking algorithm for speech enhancement" NSP Appl. Math. Inf. Sci. 9, 691-698 (2015).

3.
K. S. Kwon, H. Y Kim, and N. S. Kim, "Speech basis matrix using noise data and NMF-based speech enhancement scheme" (in Korean), J. Soc. KICS, 4, 04-02 (2015).

4.
N. Yousefian, K. Kokkinakis, and P. C. Loizou, "A coherence-based algorithm for noise reduction in dual-microphone application," in Proc, Signal Process, 1904-1908 (2010).

5.
N. Yousefian and Philipos C. Loizou, "A dual-microphone algorithm that can cope with competing-talker scenarios," IEEE Trans. Audio, Speech, Lang. Process. 21, 145-155 (2013). crossref(new window)

6.
T. Van den Bogaert, S. Doclo, J. Wouters, and M. Moonen, "Speech enhancement with multichannel Wiener filter techniques in multi-microphone binaural hearing aids," J. Acoust Soc. Am. 125, 360-371, (Jan. 2009). crossref(new window)

7.
R. L. Bouquin-Jeannes, A. A. Azirani, and G. Faucon, "Enhancement of speech degraded by coherent and inchoherent noise using a cross-spectral estimator," IEEE Trans. Speech Audio process. 5, 484-487 (Sep. 1997). crossref(new window)

8.
R. L. Bouquin-jeannes and G. Faucon, "Using the coherence function for noise reduction," Proceedings of the IEEE. 139, 276-280 (1992).

9.
M. Brandstein and D. Ward, "Microphone arrays: signal processing techniques and applications." in handbook of Microphone Arrays, edited by Brandstein (Springer-Verlog, Berlin, 2011).

10.
ITU-T Recommendation, Perceptual evaluation of speech quality(PESQ), an objective method for end-to-end speech quality assessment of narrow-band telephone networks and speech codecs, 2011.