A frequency domain noise cancelling preprocessor for narrowband speech communications systems

Preuss, R.

doi:10.1109/icassp.1979.1170757

Cited by 17 publications

(7 citation statements)

References 6 publications

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“…By combining (9) and (10), substituting for , and taking into account that only Branch (I) and (II) of (9) must be modified, we obtain the set of equations shown in (12), at the bottom of the page, where, as was mentioned, Branches (III) and (IV) of (9) are not involved in the enhancement process, since they do not contribute to audible noise components. By substituting (11) for into (12), we obtain (13), shown at the bottom of the page, where, hereafter, the common condition in Branches (I) and (II) of (12) will be omitted for simplicity.…”

Section: Parameter Estimation For Psychoacoustic Modificationmentioning

confidence: 99%

“…By solving (13), and since is positive, the following solutions are obtained as shown in (14), shown at the bottom of the next page. Note, however, that it is not desirable to estimate the parameters and for every spectral component , because in this way the estimation will be very if and (I) if and (II)…”

Section: Parameter Estimation For Psychoacoustic Modificationmentioning

confidence: 99%

See 1 more Smart Citation

Speech enhancement based on audible noise suppression

Tsoukalas

Mourjopoulos

Kokkinakis

1997

IEEE Trans. Speech Audio Process.

145

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A novel speech enhancement technique is presented based on the definition of the psychoacoustically derived quantity of audible noise spectrum and its subsequent suppression using optimal nonlinear filtering of the short-time spectral amplitude (STSA) envelope. The filter operates with sparse spectral estimates obtained from the STSA, and, when these parameters are accurately known, significant intelligibility gains, up to 40%, result in the processed speech signal. These parameters can be also estimated from noisy data, resulting into smaller but significant intelligibility gains.

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Section: Parameter Estimation For Psychoacoustic Modificationmentioning

confidence: 99%

Section: Parameter Estimation For Psychoacoustic Modificationmentioning

confidence: 99%

Speech enhancement based on audible noise suppression

Tsoukalas

Mourjopoulos

Kokkinakis

1997

IEEE Trans. Speech Audio Process.

145

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show abstract

“…In this approach a spectral decomposition of a frame of noisy speech is performed and a particular spectra l line is attenuated depending on how much the measured speech plus noise power exceeds an estimate of the background noise power . [9][10][11][12][13] …”

Section: E X I N G T O N M a S S A C H U S E T T Smentioning

confidence: 99%

“…Modifications of this algorithm have been studied extensively by Boll [10], Preuss [ 12] * and Berouti, et al [13].…”

mentioning

confidence: 99%

Speech Enhancement Using a Soft-Decision Maximum Likelihood Noise Suppression Filter.

McAulay¹,

Malpass²

1979

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“…The time domain speech waveform of a voiced speech signal is periodic, and the pitch period is the inverse of the fundamental frequency. Therefore, the following techniques were introduced using this feature: (1) adaptive comb filtering [15]; (2) harmonic selection [16]; and (3) adaptive noise cancelling techniques [17,18].…”

Section: Review Of Speech Enhancement Techniquesmentioning

confidence: 99%

Two-channel noise reduction and post-processing for speech enhancement

Zhang¹

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This thesis is focused on speech enhancement techniques based on short-time spectral amplitude (STSA) estimation. Some common STSA estimation methods and the-order minimum mean-square error (MMSE) estimation technique incorporating auditory masking properties (-masking in short) are reviewed. A word pair recognition accuracy test is done to assess the intelligibility of the-masking enhanced speech signals. Though the-masking technique outperforms most of the existing STSA estimation speech enhancement methods, some slight tonal distortion is audible in the processed speech signals when the background noise level is very high, because some speech spectral components are over-attenuated while some are not due to the enhancement algorithm. Two post-processing techniques are proposed to improve the quality of the single-channel-masking enhanced speech signals. One technique involves non-linear high-frequency regeneration, which uses the lower-band spectral information to re-synthesize the upper-band spectral structure. The other technique involves resynthesis of the weak spectral components using the autocorrelations of the strong spectral components. With the increasing use of mobile communication, a two-channel speech enhancement method for communication in a car environment is also studied. To achieve a better performance, the single-channel-masking method is incorporated within the two-channel enhancement system. The resulting output speech signals have low background noise and the distortion to the speech components is also very low, thus achieving an overall very satisfactory speech enhancement performance.

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A frequency domain noise cancelling preprocessor for narrowband speech communications systems

Cited by 17 publications

References 6 publications

Speech enhancement based on audible noise suppression

Speech enhancement based on audible noise suppression

Speech Enhancement Using a Soft-Decision Maximum Likelihood Noise Suppression Filter.

Two-channel noise reduction and post-processing for speech enhancement

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