Comparative Evaluation of Single-Channel MMSE-Based Noise Reduction Schemes for Speech Recognition

Joint Authors

Rotili, Rudy
Principi, Emanuele
Piazza, Francesco
Squartini, Stefano
Cifani, Simone

Source

Journal of Electrical and Computer Engineering

Issue

Vol. 2010, Issue 2010 (31 Dec. 2010), pp.1-6, 6 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2010-03-28

Country of Publication

Egypt

No. of Pages

6

Main Subjects

Engineering Sciences and Information Technology
Information Technology and Computer Science

Abstract EN

One of the big challenges in the field of Automatic Speech Recognition (ASR) consists in developing suitable solutions able to work properly also in adverse acoustic conditions, like in presence of additive noise and/or in reverberant rooms.

Recently a certain attention has been paid to deeply integrate the noise suppressor in the feature extraction pipeline.

In this paper, different single-channel MMSE-based noise reduction schemes have been implemented both in the frequency and cepstral domains and the related recognition performances evaluated on the AURORA2 and AURORA4 databases, therefore providing a useful reference for the scientific community.

American Psychological Association (APA)

Principi, Emanuele& Cifani, Simone& Rotili, Rudy& Squartini, Stefano& Piazza, Francesco. 2010. Comparative Evaluation of Single-Channel MMSE-Based Noise Reduction Schemes for Speech Recognition. Journal of Electrical and Computer Engineering،Vol. 2010, no. 2010, pp.1-6.
https://search.emarefa.net/detail/BIM-511749

Modern Language Association (MLA)

Principi, Emanuele…[et al.]. Comparative Evaluation of Single-Channel MMSE-Based Noise Reduction Schemes for Speech Recognition. Journal of Electrical and Computer Engineering No. 2010 (2010), pp.1-6.
https://search.emarefa.net/detail/BIM-511749

American Medical Association (AMA)

Principi, Emanuele& Cifani, Simone& Rotili, Rudy& Squartini, Stefano& Piazza, Francesco. Comparative Evaluation of Single-Channel MMSE-Based Noise Reduction Schemes for Speech Recognition. Journal of Electrical and Computer Engineering. 2010. Vol. 2010, no. 2010, pp.1-6.
https://search.emarefa.net/detail/BIM-511749

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-511749