ROBUST RECOGNITION OF DIRECT AND TELEPHONY SPEECH USING PROPER EXTRACTION OF FEATURE VECTORS AND THEIR MODIFICATION BY NEURAL NETWORKS INVERSION

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.

VALI MANSOUR; SEYED SALEHI A.

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

Journal Paper

Paper Information

Journal: NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, A- MUHANDISI -I BARQ Year:2006 | Volume:4 | Issue:1 Page(s): 21-29

Download Full-Text

Persian Verion

View:

857

Download:

Cites:

Information Journal Paper

Title

ROBUST RECOGNITION OF DIRECT AND TELEPHONY SPEECH USING PROPER EXTRACTION OF FEATURE VECTORS AND THEIR MODIFICATION BY NEURAL NETWORKS INVERSION

Author(s)

VALI MANSOUR | SEYED SALEHI A. | Issue Writer Certificate

Keywords

ROBUST SPEECH RECOGNITIONQ2

NEURAL NETWORKQ4

INVERSIONQ2

FEATURE VECTORSQ4

Abstract

A vast amount of research is going on for design of ROBUST SPEECH RECOGNITION in to alleviate speech variability conditions. One of the variability aspects is the difference between telephony speech and direct speech (recorded in noise free conditions). In this paper by using a set of experiments, it is shown that LHCB parameters are superior to traditional MFCCs for speech recognition applications when they are used in a NEURAL NETWORK based speech recognition system for both direct and telephony speech. Then by extraction of LHCBs from direct and telephony speech, and training of a MLP based speech recognition model, a direct and telephony speech recognition system is developed. Using a NEURAL NETWORK INVERSION based on gradient descent method, the telephony speech FEATURE VECTORS are modified toward to the direct speech FEATURE VECTORS and by training a second network on modified telephony and direct speech FEATURE VECTORS a 1.4% enhancement on speech recognition was achieved. Later, using general INVERSION method of NEURAL NETWORKs both telephony and direct speech FEATURE VECTORS are modified in a manner which mainly contains phonetic information and not other speech variations. Then by the training of the second NEURAL NETWORK on this dataset, the system achieved 2.98% and 1.68% higher recognition rate for direct and telephony speech, respectively.

Cites

No record.

References

No record.

Cite

APA: Copy

VALI, MANSOUR, & SEYED SALEHI, A.. (2006). ROBUST RECOGNITION OF DIRECT AND TELEPHONY SPEECH USING PROPER EXTRACTION OF FEATURE VECTORS AND THEIR MODIFICATION BY NEURAL NETWORKS INVERSION. NASHRIYYAH-I MUHANDESI-I BARQ VA MUHANDESI-I KAMPYUTAR-I IRAN (PERSIAN), 4(1), 21-29. SID. https://sid.ir/paper/53747/en

Vancouver: Copy

VALI MANSOUR, SEYED SALEHI A.. ROBUST RECOGNITION OF DIRECT AND TELEPHONY SPEECH USING PROPER EXTRACTION OF FEATURE VECTORS AND THEIR MODIFICATION BY NEURAL NETWORKS INVERSION. NASHRIYYAH-I MUHANDESI-I BARQ VA MUHANDESI-I KAMPYUTAR-I IRAN (PERSIAN)[Internet]. 2006;4(1):21-29. Available from: https://sid.ir/paper/53747/en

IEEE: Copy

MANSOUR VALI, and A. SEYED SALEHI, “ROBUST RECOGNITION OF DIRECT AND TELEPHONY SPEECH USING PROPER EXTRACTION OF FEATURE VECTORS AND THEIR MODIFICATION BY NEURAL NETWORKS INVERSION,” NASHRIYYAH-I MUHANDESI-I BARQ VA MUHANDESI-I KAMPYUTAR-I IRAN (PERSIAN), vol. 4, no. 1, pp. 21–29, 2006, [Online]. Available: https://sid.ir/paper/53747/en

Related Journal Papers