Non-Causal Time-Domain Filters for Single-Channel Noise Reduction

Research output: Contribution to journalJournal articleResearchpeer-review

10 Citations (Scopus)
681 Downloads (Pure)

Abstract

In many existing time-domain filtering methods for noise reduction in, e.g., speech processing, the filters are causal. Such causal filters can be implemented directly in practice. However, it is possible to improve the performance of such noise reduction filtering methods in terms of both noise suppression and signal distortion by allowing the filters to be non-causal. Non-causal time-domain filters require knowledge of the future, and are therefore not directly implementable. If the observed signal is processed in blocks, however, the non-causal filters are implementable. In this paper, we propose such non-causal time-domain filters for noise reduction in speech applications. We also propose some performance measures that enable us to evaluate the performance of non-causal filters. Moreover, it is shown how some of the filters can be updated recursively. Using the recursive expressions, it is also shown that the output SNRs of the filters always increase as we increase the length of the filter when the desired signal is stationary. From both the theoretical and practical evaluations of the filters, it is clearly shown that the performance of time-domain filtering methods for noise reduction can be improved by introducing non-causality.
Original languageEnglish
JournalI E E E Transactions on Audio, Speech and Language Processing
Volume20
Issue number5
Pages (from-to)1526-1541
Number of pages16
ISSN1558-7916
DOIs
Publication statusPublished - 2012

Fingerprint

channel noise
Noise abatement
noise reduction
filters
Signal distortion
Speech processing
Acoustic noise
signal distortion

Cite this

@article{4ade6764adc74b4ebf4510c54f5e6bce,
title = "Non-Causal Time-Domain Filters for Single-Channel Noise Reduction",
abstract = "In many existing time-domain filtering methods for noise reduction in, e.g., speech processing, the filters are causal. Such causal filters can be implemented directly in practice. However, it is possible to improve the performance of such noise reduction filtering methods in terms of both noise suppression and signal distortion by allowing the filters to be non-causal. Non-causal time-domain filters require knowledge of the future, and are therefore not directly implementable. If the observed signal is processed in blocks, however, the non-causal filters are implementable. In this paper, we propose such non-causal time-domain filters for noise reduction in speech applications. We also propose some performance measures that enable us to evaluate the performance of non-causal filters. Moreover, it is shown how some of the filters can be updated recursively. Using the recursive expressions, it is also shown that the output SNRs of the filters always increase as we increase the length of the filter when the desired signal is stationary. From both the theoretical and practical evaluations of the filters, it is clearly shown that the performance of time-domain filtering methods for noise reduction can be improved by introducing non-causality.",
author = "Jensen, {Jesper Rindom} and Jacob Benesty and Christensen, {Mads Gr{\ae}sb{\o}ll} and Jensen, {S{\o}ren Holdt}",
year = "2012",
doi = "10.1109/TASL.2012.2183872",
language = "English",
volume = "20",
pages = "1526--1541",
journal = "IEEE/ACM Transactions on Audio, Speech, and Language Processing",
issn = "2329-9290",
publisher = "IEEE Signal Processing Society",
number = "5",

}

Non-Causal Time-Domain Filters for Single-Channel Noise Reduction. / Jensen, Jesper Rindom; Benesty, Jacob; Christensen, Mads Græsbøll; Jensen, Søren Holdt.

In: I E E E Transactions on Audio, Speech and Language Processing, Vol. 20, No. 5, 2012, p. 1526-1541.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Non-Causal Time-Domain Filters for Single-Channel Noise Reduction

AU - Jensen, Jesper Rindom

AU - Benesty, Jacob

AU - Christensen, Mads Græsbøll

AU - Jensen, Søren Holdt

PY - 2012

Y1 - 2012

N2 - In many existing time-domain filtering methods for noise reduction in, e.g., speech processing, the filters are causal. Such causal filters can be implemented directly in practice. However, it is possible to improve the performance of such noise reduction filtering methods in terms of both noise suppression and signal distortion by allowing the filters to be non-causal. Non-causal time-domain filters require knowledge of the future, and are therefore not directly implementable. If the observed signal is processed in blocks, however, the non-causal filters are implementable. In this paper, we propose such non-causal time-domain filters for noise reduction in speech applications. We also propose some performance measures that enable us to evaluate the performance of non-causal filters. Moreover, it is shown how some of the filters can be updated recursively. Using the recursive expressions, it is also shown that the output SNRs of the filters always increase as we increase the length of the filter when the desired signal is stationary. From both the theoretical and practical evaluations of the filters, it is clearly shown that the performance of time-domain filtering methods for noise reduction can be improved by introducing non-causality.

AB - In many existing time-domain filtering methods for noise reduction in, e.g., speech processing, the filters are causal. Such causal filters can be implemented directly in practice. However, it is possible to improve the performance of such noise reduction filtering methods in terms of both noise suppression and signal distortion by allowing the filters to be non-causal. Non-causal time-domain filters require knowledge of the future, and are therefore not directly implementable. If the observed signal is processed in blocks, however, the non-causal filters are implementable. In this paper, we propose such non-causal time-domain filters for noise reduction in speech applications. We also propose some performance measures that enable us to evaluate the performance of non-causal filters. Moreover, it is shown how some of the filters can be updated recursively. Using the recursive expressions, it is also shown that the output SNRs of the filters always increase as we increase the length of the filter when the desired signal is stationary. From both the theoretical and practical evaluations of the filters, it is clearly shown that the performance of time-domain filtering methods for noise reduction can be improved by introducing non-causality.

UR - http://www.scopus.com/inward/record.url?scp=84858630828&partnerID=8YFLogxK

U2 - 10.1109/TASL.2012.2183872

DO - 10.1109/TASL.2012.2183872

M3 - Journal article

VL - 20

SP - 1526

EP - 1541

JO - IEEE/ACM Transactions on Audio, Speech, and Language Processing

JF - IEEE/ACM Transactions on Audio, Speech, and Language Processing

SN - 2329-9290

IS - 5

ER -