Conference Paper

Extension of the multi-channel Wiener filter with ITD cues for noise reduction in binaural hearing aids

Dept. of Electr. Eng., Katholieke Univ., Leuven
DOI: 10.1109/ASPAA.2005.1540171 Conference: Applications of Signal Processing to Audio and Acoustics, 2005. IEEE Workshop on
Source: IEEE Xplore


This paper presents a novel extension of the multi-channel Wiener filter (MWF) for noise reduction in binaural hearing aids, taking into account binaural localisation cues. By adding a term related to the interaural time difference (ITD) cue of the noise component to the cost function of the MWF, both the ITD cues of the speech and the noise component can be preserved, in addition to significantly improving the signal-to-noise ratio of the microphone signals

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    • "Moreover, it requires the a priori knowledge about the interaural time and level differences of the source signal, which is difficult if not impossible to acquire in many applications such as teleconferencing. The third category is through the use of multichannel noise reduction principles such as the transfer function based generalized sidelobe canceller (TF-GSC) [17], the multichannel Wiener filter [18], and the spatio-temporal prediction method [19]. Since the multichannel noise reduction techniques are formulated to estimate the desired signals observed at the microphones, the spatial information should be naturally preserved . "
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    ABSTRACT: This paper deals with the problem of noise reduction in stereo sound systems where the objective is not only to reduce noise, but also to preserve the spatial information of both the desired speech and noise sources so that the listener can still localize the speech and noise sources by listening to the enhanced binaural outputs. To achieve this objective, we use the widely linear (WL) framework developed previously and convert the problem of binaural noise reduction into one of monaural filtering with complex signals. We then present a way to decompose both the complex speech and noise signal vectors into two orthogonal components: one correlated and the other uncorrelated with the corresponding current signal sample. With this decomposition, the problem of noise reduction with preservation of the spatial information of speech and noise sources is formulated as an optimization problem with two constraints: one on the desired speech and the other on the preservation of the noise signal. We then derive a WL linearly constrained minimum variance (LCMV) filter, which can take advantage of the statistics and noncircularity of the complex speech signal to achieve noise reduction. In contrast to the WL Wiener and minimum variance distortionless response (MVDR) filters developed previously that can only preserve the characteristics and spatial information of the desired sound source, this new WL LCMV filter has the potential to reduce noise while preserving the characteristics and spatial information of both the desired and noise sources at the same time. Experimental results are provided to justify the claimed merits of the proposed WL LCMV filter.
    IEEE Transactions on Audio Speech and Language Processing 07/2013; 21(7):1343-1354. DOI:10.1109/TASL.2013.2248719 · 2.48 Impact Factor
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    • "Alternatively, instead of trying to determine a common gain, in a specific class of optimal multichannel frequency-domain algorithms (namely the Multichannel Wiener Filter), some solutions exist ([9] [10] [11], and other works cited in [11]) which instead try and constrain complex Wiener gains to minimize additional components in the global cost function which are aimed at reducing interaural time or level differences; however , we see some drawbacks in [9] [10] [11]: first the solutions are tailored to a binaural hearing aid configuration; next they require a potentially complex iterative optimization scheme for each incoming frame of noisy samples [11]. Finally, as reported in [11] in an extensive analysis, these solutions may not be robust to multiple-noise-source scenarios. "
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    ABSTRACT: It is often very important for multichannel speech enhancement systems, such as hearing aids, to preserve spatial impressions. Usually, this is achieved by first designing a particular speech enhancement algorithm and later or separately constraining the obtained solution to respect spatial cues. Instead, we propose in this paper to conduct the entire system's design via the minimization of statistical spectral distances seen as functions of a real-valued, common gain to be applied to all channels in the frequency-domain. For various spectral distances, we show that the gain derived is expressible in terms of optimal multichannel spectral amplitude estimators (such as the multichannel Minimum Mean Squared Error Spectral Amplitude Estimator, among others). In addition, we report experimental results in complex environments (i.e., including reverberation, interfering talkers, and low signal-to-noise ratio), showing the potential of the proposed methods against recent state-of-the-art multichannel enhancement setups which preserve spatial cues as well.
    Signal Processing 01/2013; 93(1):321–325. DOI:10.1016/j.sigpro.2012.06.024 · 2.21 Impact Factor
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    • "In this case, authors included an extra term to the cost function to preserve the interaural time difference (ITD), which is an important cue used by the human auditory system for localization. Since the MWF method proposed in [12] is computationally expensive, Klasen et al. [13] proposed a simplification known as MWF-N (MWF with partial noise). The ability of MWF-N to preserve simultaneously the localization cues for the target and interfering signals is demonstrated through subjective tests [18] and theoretical analysis [19]. "
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    ABSTRACT: Different noise-reduction methods have been proposed in the literature for single and multiple-microphone applications. For binaural hearing aids, multiple-microphone noise-reduction methods offer two significant psycho-acoustical advantages with respect to the single-microphone methods. First, noise reduction strategies based on binaural processing (processing using the information received at the left and right ear) are more effective than using independent monaural processing because of the added information. Second, there is an user preference for noise reduction methods that preserve localization cues of both target and interfering signals. Although different multiple-microphone noise-reduction techniques have been proposed in the literature, only a small set is able to preserve the localization cues for both target and interfering signals. This paper proposes a binaural noise-reduction method that preserves the localization cues for both target and interfering signals. The proposed method is based on blind source separation (BSS) followed by a postprocessing technique inspired by a human auditory model. The performance of the proposed method is analyzed using objective and subjective measurements, and compared to existing binaural noise-reduction methods based on BSS and multichannel Wiener filter (MWF). Results show that for some scenarios and conditions, the proposed method outperforms on average the existing methods in terms of noise reduction and provides nearly similar sound quality.
    IEEE Transactions on Audio Speech and Language Processing 05/2012; 20(4):1372-1382. DOI:10.1109/TASL.2011.2179295 · 2.48 Impact Factor
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