An improved post-filter of acoustic echo canceller based on subband implementation

In this paper, an effective post-filter structure for subband-based acoustic echo cancellation (SAEC) is proposed. Compared with the current subband-based post-filters, the proposed one can more consistently suppress the background noise, as well as the residual echoes. To reduce the effects of the distortion of the near-end speech, two alternative modified versions of the post-filter are proposed, which guarantees the quality of speech communications. The proposed post-filters are seamlessly combined with the subband-based AEC system with quite small computational burden. The instrumental evaluation and listening test both demonstrate the superiority of the post-filters.     

Time-domain noise reduction based on an orthogonal decomposition for desired signal extraction

This paper addresses the problem of noise reduction in the time domain where the clean speech sample at every time instant is estimated by filtering a vector of the noisy speech signal. Such a clean speech estimate consists of both the filtered speech and residual noise (filtered noise) as the noisy vector is the sum of the clean speech and noise vectors. Traditionally, the filtered speech is treated as the desired signal after noise reduction. This paper proposes to decompose the clean speech vector into two orthogonal components: one is correlated and the other is uncorrelated with the current clean speech sample. While the correlated component helps estimate the clean speech, it is shown that the uncorrelated component interferes with the estimation, just as the additive noise. Based on this orthogonal decomposition, the paper presents a way to define the error signal and cost functions and addresses the issue of how to design different optimal noise reduction filters by optimizing these cost functions. Specifically, it discusses how to design the maximum SNR filter, the Wiener filter, the minimum variance distortionless response (MVDR) filter, the tradeoff filter, and the linearly constrained minimum variance (LCMV) filter. It demonstrates that the maximum SNR, Wiener, MVDR, and tradeoff filters are identical up to a scaling factor. It also shows from the orthogonal decomposition that many performance measures can be defined, which seem to be more appropriate than the traditional ones for the evaluation of the noise reduction filters.     

基于能量损失率估计的传声器阵列语音增强

在延时相加波束形成和维纳滤波技术的基础上,提出了一种基于能量损失率估计的传声器阵列后滤波语音增强算法。该算法通过检测线性不等间距传声器阵列中各嵌套子阵在波束形成前后的能量变化来估计维纳滤波器的权系数,实现了语音增强的目标。在仿真数据集上的实验评估表明,相比原始语音,该算法增强后的语音在信噪比、对数谱距离和感知质量等指标上平均分别改善了17.1 dB,1.001和0.935,具有很好的应用前景。      

An iterative noise cross-PSD estimation for two-microphone speech enhancement

Among various speech enhancement methods, dual-microphone methods are of a great importance for their low cost implementation and for exploiting spatial-filtering benefits of the microphone arrays. Coherence based methods are well-known as efficient two-microphone noise reduction techniques. These techniques do not work well, when received noise signals are correlated. These can be improved when the cross power spectral density (CPSD) of noise is available. In this paper, we propose an iterative approach for estimation of the noise CPSD to be employed in coherence based methods. We compare the proposed iterative noise CPSD estimation with a noise CPSD estimation technique based on voice activity detector (VAD), both of which are employed in a two-microphone speech enhancement, separately. Evaluation results show that the two-microphone speech enhancement scheme utilizing the proposed noise CPSD estimation technique performs superior than the enhancement system using the VAD-based noise CPSD estimation.     

On the efficacy of spatial sampling using manual scanning paths to determine the spatial average sound pressure level in rooms

In architectural acoustics, noise control and environmental noise, there are often steady-state signals for which it is necessary to measure the spatial average, sound pressure level inside rooms. This requires using fixed microphone positions, mechanical scanning devices, or manual scanning. In comparison with mechanical scanning devices, the human body allows manual scanning to trace out complex geometrical paths in three-dimensional space. To determine the efficacy of manual scanning paths in terms of an equivalent number of uncorrelated samples, an analytical approach is solved numerically. The benchmark used to assess these paths is a minimum of five uncorrelated fixed microphone positions at frequencies above 200 Hz. For paths involving an operator walking across the room, potential problems exist with walking noise and non-uniform scanning speeds. Hence, paths are considered based on a fixed standing position or rotation of the body about a fixed point. In empty rooms, it is shown that a circle, helix, or cylindrical-type path satisfy the benchmark requirement with the latter two paths being highly efficient at generating large number of uncorrelated samples. In furnished rooms where there is limited space for the operator to move, an efficient path comprises three semicircles with 45°-60° separations.     

The effect of multimicrophone noise reduction systems on sound source localization by users of binaural hearing aids

This paper evaluates the influence of three multimicrophone noise reduction algorithms on the ability to localize sound sources. Two recently developed noise reduction techniques for binaural hearing aids were evaluated, namely, the binaural multichannel Wiener filter (MWF) and the binaural multichannel Wiener filter with partial noise estimate (MWF-N), together with a dual-monaural adaptive directional microphone (ADM), which is a widely used noise reduction approach in commercial hearing aids. The influence of the different algorithms on perceived sound source localization and their noise reduction performance was evaluated. It is shown that noise reduction algorithms can have a large influence on localization and that (a) the ADM only preserves localization in the forward direction over azimuths where limited or no noise reduction is obtained; (b) the MWF preserves localization of the target speech component but may distort localization of the noise component. The latter is dependent on signal-to-noise ratio and masking effects; (c) the MWF-N enables correct localization of both the speech and the noise components; (d) the statistical Wiener filter approach introduces a better combination of sound source localization and noise reduction performance than the ADM approach.     

基于双传声器的蓝牙耳机降噪算法

用于免提通信设备的语音增强算法一直是研究的热点问题,而算法处理结果的音质问题近年来也备受关注。针对基于双传声器降噪的蓝牙耳机系统,将常用多通道传声器降噪算法归纳为基于相干函数法和基于空间预分离法这两大类进行分析和比较。基于相干函数法利用两个通道间信号的相干函数对含噪信号滤波达到降噪目的,而基于空间预分离法利用空间特性从含噪信号中分离出噪声参考信号来消除噪声。分析基于降噪量、语音音质和综合性能三个指标,从约束语音损伤的角度分析最优解的形式,并对比两类算法的实际性能。结果表明选择合适的算法可权衡降噪量与语音损伤,达到较好的综合性能。     

Time-delay estimation of reverberated speech exploiting harmonic structure.

The relative time delay associated with a speech signal received at a pair of spatially separated microphones is a key component in talker localization and microphone array beamforming procedures. The traditional method for estimating this parameter utilizes the generalized cross correlation (GCC), the performance of which is compromised by the presence of room reverberations and background noise. Typically, the GCC filtering criteria used are either focused on the signal degradations due to additive noise or those due exclusively to multipath channel effects. There has been relatively little success at applying GCC weighting schemes which are robust to both of these conditions. This paper details an alternative approach which attempts to employ a signal-dependent criterion, namely, the estimated periodicity of the speech signal, to design a GCC filter appropriate for the combination of noise and multipath distortions. Simulations are performed across a range of room conditions to illustrate the utility of the proposed time-delay estimation method relative to conventional GCC filtering approaches.     

Single-channel speech enhancement method using reconstructive NMF with spectrotemporal speech presence probabilities

In this paper, a novel single microphone channel-based speech enhancement technique is presented. While most of the conventional nonnegative matrix factorization-based approaches focus on generating a basis matrix of speech and noise for enhancement, the proposed algorithm performs an additional process to reconstruct speech from noisy speech when these two elements are highly overlapped in selected spectral bands. This process involves a log-spectral amplitude based estimator, which provides the spectrotemporal speech presence probability to obtain a more accurate reconstruction. Moreover, the proposed algorithm applies an unsupervised learning method to the input noise, so it is adaptable to any type of environmental noise without a pre-trained dictionary. The experimental results demonstrate that the proposed algorithm obtains improved speech enhancement performance compared with conventional single channel-based approaches.     

Effects of directional microphone and adaptive multichannel noise reduction algorithm on cochlear implant performance

Although cochlear implant (CI) users have enjoyed good speech recognition in quiet, they still have difficulties understanding speech in noise. We conducted three experiments to determine whether a directional microphone and an adaptive multichannel noise reduction algorithm could enhance CI performance in noise and whether Speech Transmission Index (STI) can be used to predict CI performance in various acoustic and signal processing conditions. In Experiment I, CI users listened to speech in noise processed by 4 hearing aid settings: omni-directional microphone, omni-directional microphone plus noise reduction, directional microphone, and directional microphone plus noise reduction. The directional microphone significantly improved speech recognition in noise. Both directional microphone and noise reduction algorithm improved overall preference. In Experiment II, normal hearing individuals listened to the recorded speech produced by 4- or 8-channel CI simulations. The 8-channel simulation yielded similar speech recognition results as in Experiment I, whereas the 4-channel simulation produced no significant difference among the 4 settings. In Experiment III, we examined the relationship between STIs and speech recognition. The results suggested that STI could predict actual and simulated CI speech intelligibility with acoustic degradation and the directional microphone, but not the noise reduction algorithm. Implications for intelligibility enhancement are discussed.