INPUT SNR ESTIMATION USING BINARY MASK IN SYSTEMS BASED ON COMPUTATIONAL AUDITORY SCENE ANALYSIS

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

GERAVANCHIZADEH M.; DADVAR P.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: TABRIZ JOURNAL OF ELECTRICAL ENGINEERING Year:2016 | Volume:46 | Issue:2 (76) Page(s): 187-196

Download Full-Text

Persian Verion

View:

1,019

Download:

Cites:

Information Journal Paper

Title

INPUT SNR ESTIMATION USING BINARY MASK IN SYSTEMS BASED ON COMPUTATIONAL AUDITORY SCENE ANALYSIS

Author(s)

GERAVANCHIZADEH M. | DADVAR P. | Issue Writer Certificate

Keywords

SNR ESTIMATIONQ2

SIGNAL-TO-NOISE RATIOQ2

COMPUTATIONAL AUDITORY SCENE ANALYSIS (CASA)Q2

IDEAL BINARY MASK (IBM)Q2

Abstract

This paper presents a new approach for estimating the SIGNAL-TO-NOISE RATIO (SNR) of mixture signal, which is based on the computational auditory scene analysis (CASA). The ideal binary mask (IBM) which is generally the computational goal of CASA based systems is used to estimate the SNR of noisy speech signal. The proposed method is evaluated using IBM and some quasi-IBM masks. The method is simple and computationally efficient. Systematic evaluations show that the proposed method results in reasonable estimation of the input SNR level in a wide range of SNR values, and probable errors in estimating IBM do not affect so much the performance of the proposed system. Furthermore, simulation results show that the proposed system outperforms previous SNR ESTIMATION methods.

Cites

No record.

References

No record.

Cite

APA: Copy

GERAVANCHIZADEH, M., & DADVAR, P.. (2016). INPUT SNR ESTIMATION USING BINARY MASK IN SYSTEMS BASED ON COMPUTATIONAL AUDITORY SCENE ANALYSIS. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 46(2 (76)), 187-196. SID. https://sid.ir/paper/256419/en

Vancouver: Copy

GERAVANCHIZADEH M., DADVAR P.. INPUT SNR ESTIMATION USING BINARY MASK IN SYSTEMS BASED ON COMPUTATIONAL AUDITORY SCENE ANALYSIS. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING[Internet]. 2016;46(2 (76)):187-196. Available from: https://sid.ir/paper/256419/en

IEEE: Copy

M. GERAVANCHIZADEH, and P. DADVAR, “INPUT SNR ESTIMATION USING BINARY MASK IN SYSTEMS BASED ON COMPUTATIONAL AUDITORY SCENE ANALYSIS,” TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, vol. 46, no. 2 (76), pp. 187–196, 2016, [Online]. Available: https://sid.ir/paper/256419/en

Related Journal Papers