Binaural noise PSD estimation for binaural speech enhancement

Azarpour, Masoumeh; Enzner, Gerald; Martin, Rainer

doi:10.1109/icassp.2014.6854971

Cited by 7 publications

(17 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To simplify the equations, the noise PSDs at the left and right ear are considered to be equal. In [41], it was shown that for measured noise signals, the assumptions of equal noise PSDs at the two microphones are more plausible at low frequencies than at high frequencies. Assuming equal noise PSDs, i.e., n l n l = n r n r = n at the two microphones, the cross PSD, n l n r in (15), consequently can be expressed based on the left and right noise PSDs and the coherence function, i.e., n r n l = n l n r = n l n r n , therein considering that the noise coherence of a diffuse noise field is real valued.…”

Section: Diffuse Noisementioning

confidence: 99%

“…The interaural transfer function (ITF) estimation errors, subject to minimization, are written as [41] …”

Section: Itf-based Adaptive Blocking (Itfb)mentioning

confidence: 99%

“…In [42], we proposed to employ a blind system identification approach based on the crossrelation error minimization to estimate the noise PSD using the cross-relation residual. The successful application of the estimated noise power for speech enhancement was initially demonstrated in [41,42] with hearing aid application.…”

Section: Introductionmentioning

confidence: 99%

“…A spectral correction gain function based on the BSS de-mixing matrix was derived to reduce the bias of the estimated noise PSD. In [41], we proposed a binaural noise PSD estimator based on the equalization-cancelation technique. The target speech signal is equalized and canceled by two independent leastmean-square (LMS)-type algorithms for the left and right noise PSD estimation.…”

Section: Introductionmentioning

confidence: 99%

“…This includes the interaural transfer function blockingbased noise PSD estimator (ITFB) [41] (Fig. 2a) and the cross-relation-based noise PSD estimators (CRB) [42] (Fig.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Binaural noise reduction via cue-preserving MMSE filter and adaptive-blocking-based noise PSD estimation

Azarpour

Enzner

2017

EURASIP J. Adv. Signal Process.

Self Cite

View full text Add to dashboard Cite

Binaural noise reduction, with applications for instance in hearing aids, has been a very significant challenge. This task relates to the optimal utilization of the available microphone signals for the estimation of the ambient noise characteristics and for the optimal filtering algorithm to separate the desired speech from the noise. The additional requirements of low computational complexity and low latency further complicate the design. A particular challenge results from the desired reconstruction of binaural speech input with spatial cue preservation. The latter essentially diminishes the utility of multiple-input/single-output filter-and-sum techniques such as beamforming. In this paper, we propose a comprehensive and effective signal processing configuration with which most of the aforementioned criteria can be met suitably. This relates especially to the requirement of efficient online adaptive processing for noise estimation and optimal filtering while preserving the binaural cues. Regarding noise estimation, we consider three different architectures: interaural (ITF), cross-relation (CR), and principal-component (PCA) target blocking. An objective comparison with two other noise PSD estimation algorithms demonstrates the superiority of the blocking-based noise estimators, especially the CR-based and ITF-based blocking architectures. Moreover, we present a new noise reduction filter based on minimum mean-square error (MMSE), which belongs to the class of common gain filters, hence being rigorous in terms of spatial cue preservation but also efficient and competitive for the acoustic noise reduction task. A formal real-time subjective listening test procedure is also developed in this paper. The proposed listening test enables a real-time assessment of the proposed computationally efficient noise reduction algorithms in a realistic acoustic environment, e.g., considering time-varying room impulse responses and the Lombard effect. The listening test outcome reveals that the signals processed by the blocking-based algorithms are significantly preferred over the noisy signal in terms of instantaneous noise attenuation. Furthermore, the listening test data analysis confirms the conclusions drawn based on the objective evaluation.

show abstract

Section: Diffuse Noisementioning

confidence: 99%

“…The interaural transfer function (ITF) estimation errors, subject to minimization, are written as [41] …”

Section: Itf-based Adaptive Blocking (Itfb)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…This includes the interaural transfer function blockingbased noise PSD estimator (ITFB) [41] (Fig. 2a) and the cross-relation-based noise PSD estimators (CRB) [42] (Fig.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations