AN INTRODUCTION OF NEW DESICA ALGORITHM FOR BLIND SPEECH SEPARATION IN DYNAMIC CASE

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.

MAHDIKHANI MAHDI; KAHAEI MOHAMMAD HOSSEIN

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

Journal Paper

Paper Information

Journal: SIGNAL AND DATA PROCESSING Year:2009 | Volume:- | Issue:2 (SERIAL 12) Page(s): 63-74

Download Full-Text

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

Persian Verion

View:

711

Download:

Cites:

Information Journal Paper

Title

AN INTRODUCTION OF NEW DESICA ALGORITHM FOR BLIND SPEECH SEPARATION IN DYNAMIC CASE

Author(s)

MAHDIKHANI MAHDI | KAHAEI MOHAMMAD HOSSEIN | Issue Writer Certificate

Keywords

BLIND SOURCE SEPARATIONQ3

EVENTUAL THRESHOLDINGQ3

BINARY MASKQ3

Abstract

We consider a new scenario in blind speech separation problem in which the number and the features of active sources change with time in opposite to the previous methods in which all sources are active all the time. Accordingly, we propose the new DESICA algorithm for source separation which is a compound of the ICA and DESPRIT algorithms. In this algorithm, using the ICA, the separation process is performed initially and then using the DESPRIT algorithm, the BINARY MASK of silence intervals is calculated. Finally, by applying the BINARY MASK to the separated signals, the final separation is obtained. Simulation results show that the DESICA algorithm improves the SDR and SIR about 6dB compared to those of the DESPRIT algorithm. Also, the SEN is improved about 11 and 17dB with respect to those of the ICA and DESPRIT algorithms.

Cites

No record.

References

No record.

Cite

APA: Copy

MAHDIKHANI, MAHDI, & KAHAEI, MOHAMMAD HOSSEIN. (2009). AN INTRODUCTION OF NEW DESICA ALGORITHM FOR BLIND SPEECH SEPARATION IN DYNAMIC CASE. SIGNAL AND DATA PROCESSING, -(2 (SERIAL 12)), 63-74. SID. https://sid.ir/paper/160804/en

Vancouver: Copy

MAHDIKHANI MAHDI, KAHAEI MOHAMMAD HOSSEIN. AN INTRODUCTION OF NEW DESICA ALGORITHM FOR BLIND SPEECH SEPARATION IN DYNAMIC CASE. SIGNAL AND DATA PROCESSING[Internet]. 2009;-(2 (SERIAL 12)):63-74. Available from: https://sid.ir/paper/160804/en

IEEE: Copy

MAHDI MAHDIKHANI, and MOHAMMAD HOSSEIN KAHAEI, “AN INTRODUCTION OF NEW DESICA ALGORITHM FOR BLIND SPEECH SEPARATION IN DYNAMIC CASE,” SIGNAL AND DATA PROCESSING, vol. -, no. 2 (SERIAL 12), pp. 63–74, 2009, [Online]. Available: https://sid.ir/paper/160804/en

Related Journal Papers