Frequency-invariant (FI) beamforming aims at recovering signals without any distortion and maintaining spatial selectivity over the entire bandwidth. However, most existing FI beamforming ...(FIB)methods consider the weighted ℓ1-norm or modified ℓ1-norm of the filters as the objective function for sparse FIB design, which cannot assure the optimal sparse solution. To deal with this drawback, an optimization problem for the FIB design of sparse microphone array in terms of ℓp-norm (0<p<1) minimization is formulated, where distortion-less response, mainlobe and sidelobe constraints are considered. Due to the existence of the ℓp-norm objective function, the resultant problem is nonconvex, and therefore, an alternating direction method of multipliers (ADMM) algorithm is devised. Specifically, the corresponding problem is decomposed into multi-block subproblems to determine all unknown variables separately. Then, the most dominant sensor positions for each frequency are determined by using the principal component analysis (PCA) and K-mean clustering algorithm. Numerical examples show that the proposed design achieves good directivity factor, frequency invariance and better sparsity.
•A novel two-channel speech separation algorithm is proposed, focusing on the separation accuracy and robustness.•The Comb-Filter Effect is discovered and quantitatively analyzed for the first ...time.•An accurate signal estimation algorithm based on the Comb-Filter Effect is designed.•The algorithm is aimed at fixed sound source and weak reverberation environment.
In the field of speech separation, the traditional single-channel and multi-channel speech separation methods have made great progress. However, the accuracy of separation and automatic speech recognition(ASR) rate are not yet satisfactory. With the development of neural networks, some scholars began to use deep learning to achieve speech separation. Although this kind of method improves the accuracy of speech separation, it also leads to the need for pre-training the model, higher computational complexity and reduced separation performance when the model does not match the mixed signal. This paper has conducted an in-depth study on the scene of multi-speaker separation, and proposed a new dual-channel speech separation algorithm based on the Comb-Filter Effect (CFE). The CFE is an effect that occurs when a signal passes through a first-order differential microphone(FDM) array. And this effect is discovered and exploited for the first time. By using this effect, this paper designed a new signal spectrum estimation method that can realize accurate estimation of speech signal, and combined this method with traditional spectral subtraction to achieve the purpose of speech separation. Finally, this paper compared the proposed algorithm with the traditional FastICA-based algorithm and the fully-convolutional time-domain audio separation network(Conv-TasNet)-based algorithm. The results of simulation and comparison experiments show that the algorithm can effectively separate two-way speech signals while greatly reducing the computational complexity and has excellent robustness. In various situations, the proposed algorithm can obtain the Scale-Invariant Source-to-Noise Ratio improvement (SI-SNRi) of 9.19 dB on average. In addition, the Short-Time Objective Intelligibility (STOI) and Perceptual Evaluation of Speech Quality (PESQ) of the speech signal can be improved by an average of 33% and 70% or more respectively.
Differential microphone arrays (DMAs) are characterized as compact superdirective beamformers whose beampatterns are almost frequency invariant. In this work, we present a time-domain design of ...Nth-order DMAs, which is important in some applications where minimal delay is required, such as real-time audio communications. Moreover, design in the time domain can reduce the computational efforts, compared to the frequency-domain design, especially when short filters are sufficient. We present design examples for DMAs illustrating some of the fundamental properties of the time-domain implementation as well as the equivalence to the frequency-domain design approach.
Both the null-constrained method and the Jacobi-Anger expansion method are commonly adopted to design the fully steerable circular differential microphone arrays (CDMAs). So far, these two methods ...have been independently studied, and it is unclear why they exhibit pronounced performance difference and whether they have a potential connection. In this letter, we develop a unified framework for the design of the fully steerable CDMA, which jointly utilizes the null constraints and the Jacobi-Anger expansion. We show that the existing two methods can be treated as special cases of the proposed approach and they can indeed be connected. We then reveal that the null-constrained CDMA can be viewed as the regularized Jacobi-Anger expansion-based CDMA, which theoretically explains why the former can alleviate the deep nulls problem in white noise gain in certain cases and why it still suffers from the severe deep nulls in other cases. We further explain why the magnitude of the synthesized beampattern of the Jacobi-Anger expansion-based method in nulls' direction can be much larger than that of the null-constrained method. Simulations support the theoretical results well.
Performing continuous beam steering, from planar arrays of high-order differential microphones, is not trivial. The main problem is that shape-preserving beams can be steered only in a finite set of ...privileged directions, which depend on the position and the number of physical microphones. In this letter, we propose a simple and computationally inexpensive method for alleviating this problem using planar microphone arrays. Given two identical reference beams pointing in two different directions, we show how to build a beam of nearly constant shape, which can be continuously steered between such two directions. The proposed method, unlike the diffused steering approaches based on linear combinations of eigenbeams (spherical harmonics), is applicable to planar arrays also if we deal with beams characterized by high-order polar patterns. Using the coefficients of the Fourier series of the polar patterns, we also show how to find a tradeoff between shape invariance of the steered beam, and maximum angular displacement between the two reference beams. We show the effectiveness of the proposed method through the analysis of models based on first-, second-, and third-order differential microphones.
According to related research, the reasons of the users unwilling to wear assistive listening devices (ALD) is risk of unable to determine the position of sound. Additionally, the ALD proposed in ...this study can perform 360° scan and determine the position. However, it cannot determine the vertical position of the target, resulting in fluctuating volume. Therefore, this study proposes a new sensors fusion method for the space perception by the space perception module on ALD that combines computer vision technology (CV), dual-layer differential microphone arrays algorithm (d-DMA), time difference of arrival (TDOA), and Mixing Algorithm. It's primarily designed for patients with mild to moderate hearing loss, and the prototype has been developed. This device enhances the target speech (TS) and adjusts the volume output of dual-channels to achieve an immersive auditory experience through the Mixing Algorithm. This helps to mitigate the risk by inability to determine the position of sound. Furthermore, this study addressing the issue of fluctuating volume by the d-DMA. Based on results, the proposed device achieves an image accuracy rate over 94% at a normal conversation distance (<160 cm), with 30 degrees of sound reception range. Additionally, the stability of volume output is improved by 60% compared to commercially ALD. Clinical results demonstrate that the device enhances the speech recognition threshold (SRT) by 5.5 dB in quiet environments and 5.8 dB in noisy environments. Finally, participants' satisfaction with the device in both environments indicating the potential of this device for future commercialization.
In this letter, a novel time-domain implementation of robust first-order differential microphone arrays (DMAs), based on wave digital filters, is presented. The proposed beamforming method is ...extremely efficient, as it requires at most two multipliers and one delay for each filter, where the necessary number of filters equals the number of physical microphones of the array, and it avoids the use of fractional delays. The update of the coefficients of the filters, required for reshaping the beampattern, has a significantly lower computational cost with respect to the time-domain methods presented in the literature. This makes the proposed method suitable for real-time DMA applications with time-varying beampatterns.
Sound source DOA estimation using first-order differential microphone arrays (DMAs) has been demonstrated as a promising means for the applications where the size of arrays is restricted. The ...existing methods for DOA estimation of multiple speech sources with first-order DMAs, however, are shown sensitive to noise and room reverberation. To combat the problem, we propose a DOA estimation algorithm by exploring the redundancies of two orthogonal first-order DMAs in sound intensity measurement. In particular, the reliable time–frequency points for DOA estimation can be effectively singled out by the proposed algorithm and thus leads to better DOA estimation performance in noisy and reverberant environments. Moreover, the proposed algorithm has a closed form solution, and no time-consuming search process over spatial space is required. Simulation and real experimental results have demonstrated the effectiveness of the proposed algorithm.
Design of Robust Differential Microphone Arrays Liheng Zhao; Benesty, Jacob; Jingdong Chen
IEEE/ACM transactions on audio, speech, and language processing,
2014-Oct., 2014-10-00, 20141001, Letnik:
22, Številka:
10
Journal Article
Recenzirano
Differential microphone arrays (DMAs), due to their small size and enhanced directivity, are quite promising in speech enhancement applications. However, it is well known that differential ...beamformers have the drawback of white noise amplification, which is a major issue in the processing of wideband signals such as speech. In this paper, we focus on the design of robust DMAs. Based on the Maclaurin's series approximation and frequency-independent beampatterns, the robust first-, second-, and third-order DMAs are proposed by using more microphones than the order plus one, and the corresponding minimum-norm filters are derived. Compared to the traditional DMAs, the proposed designs are more robust with respect to white noise amplification while they are capable of achieving similar directional gains.
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