Effects of Bilateral Automatic Gain Control Synchronization in Cochlear Implants With and Without Head Movements: Sound Source Localization in the Frontal Hemifield

Purpose For bilaterally implanted patients, the automatic gain control (AGC) in both left and right cochlear implant (CI) processors is usually neither linked nor synchronized. At high AGC compression ratios, this lack of coordination between the two processors can distort interaural level differences, the only useful interaural difference cue available to CI patients. This study assessed the improvement, if any, in the utility of interaural level differences for sound source localization in the frontal hemifield when AGCs were synchronized versus independent and when listeners were stationary versus allowed to move their heads. Method Sound source identification of broadband noise stimuli was tested for seven bilateral CI patients using 13 loudspeakers in the frontal hemifield, under conditions where AGCs were linked and unlinked. For half the conditions, patients remained stationary; in the other half, they were encouraged to rotate or reorient their heads within a range of approximately ± 30° during sound presentation. Results In general, those listeners who already localized reasonably well with independent AGCs gained the least from AGC synchronization, perhaps because there was less room for improvement. Those listeners who performed worst with independent AGCs gained the most from synchronization. All listeners performed as well or better with synchronization than without; however, intersubject variability was high. Head movements had little impact on the effectiveness of synchronization of AGCs. Conclusion Synchronization of AGCs offers one promising strategy for improving localization performance in the frontal hemifield for bilaterally implanted CI patients. Supplemental Material https://doi.org/10.23641/asha.14681412

An investigation into high-speed train interior noise with operational transfer path analysis method

Passengers' demands for riding comfort have been getting higher and higher as the high-speed railway develops. Scientific methods to analyze the interior noise of the high-speed train are needed and the operational transfer path analysis (OTPA) method provides a theoretical basis and guidance for the noise control of the train and overcomes the shortcomings of the traditional method, which has high test efficiency and can be carried out during the working state of the targeted machine. The OTPA model is established from the aspects of "path reference point-target point" and "sound source reference point-target point". As for the mechanism of the noise transmission path, an assumption is made that the direct sound propagation is ignored, and the symmetric sound source and the symmetric path are merged. Using the operational test data and the OTPA method, combined with the results of spherical array sound source identification, the path contribution and sound source contribution of the interior noise are analyzed, respectively, from aspects of the total value and spectrum. The results show that the OTPA conforms to the calculation results of the spherical array sound source identification. At low speed, the contribution of the floor path and the contribution of the bogie sources are dominant. When the speed is greater than 300 km/h, the contribution of the roof path is dominant. Moreover, for the carriage with a pantograph, the lifted pantograph is an obvious source. The noise from the exterior sources of the train transfer into the interior mainly through the form of structural excitation, and the contribution of air excitation is non-significant. Certain analyses of train parts provide guides for the interior noise control.

A Ratio Model of L1/L2 Norm for Sound Source Identification

In the field of sound source identification, robust and accurate identification of the targeted source could be a challenging task. Most of the existing methods select the regularization parameters whose value could directly affect the accuracy of sound source identification during the solving processing. In this paper, we introduced the ratio model ℓ1/ℓ2 norm to identify the sound source(s) in the engineering field. Using the alternating direction method of multipliers solver, the proposed approach could avoid the selection of the regularization parameter and localize sound source(s) with robustness at low and medium frequencies. Compared with other three methods employing classical penalty functions, including the Tikhonov regularization method, the iterative zoom-out-thresholding algorithm and the fast iterative shrinkage-thresholding algorithm, the Monte Carlo Analysis shows that the proposed approach with ℓ1/ℓ2 model leads to stable sound pressure reconstruction results at low and medium frequencies. The proposed method demonstrates beneficial distance-adaptability and signal-to-noise ratio (SNR)-adaptability for sound source identification inverse problems.

Improving the Sound Source Identification Performance of Sparsity Constrained Deconvolution Beamforming Utilizing SFISTA

In this paper, an alternative sparsity constrained deconvolution beamforming utilizing the smoothing fast iterative shrinkage-thresholding algorithm (SFISTA) is proposed for sound source identification. Theoretical background and solving procedures are introduced. The influence of SFISTA regularization and smoothing parameters on the sound source identification performance is analyzed, and the recommended values of the parameters are obtained for the presented cases. Compared with the sparsity constrained deconvolution approach for the mapping of acoustic sources (SC-DAMAS) and the fast iterative shrinkage-thresholding algorithm (FISTA), the proposed SFISTA with appropriate regularization and smoothing parameters has faster convergence speed, higher quantification accuracy and computational efficiency, and more insensitivity to measurement noise.

Using Virtual Soundwalk Approach for Assessing Sound Art Soundscape Interventions in Public Spaces

This paper discusses the soundscape assessment approaches to soundscape interventions with musical features introduced to public spaces as permanent sound art, with a focus on the ISO 12913 series, Method A for data collection applied in a laboratory study. Three soundscape interventions in three cities are investigated. The virtual soundwalk is used to combine the benefits of the on-site and laboratory settings. Two measurement points per location were recorded—one at a position where the intervention was clearly perceptible, the other further away to serve as a baseline condition. The participants (N = 44) were exposed to acoustic environments (N = 6) recorded using the first-order Ambisonics microphone on-site and then reproduced via the second-order Ambisonics system in laboratory. A series of rank-based Kruskal–Wallis tests were performed on the results of the subjective responses. Results revealed a statistically significant positive effect on soundscape at two locations, and limitations related to sound source identification due to cultural factors and geometrical configuration of the public space at one location.

A Sound Source Identification Algorithm Based on Bayesian Compressive Sensing and Equivalent Source Method

Near-field acoustic holography (NAH) based on equivalent source method (ESM) is an effective method for identifying sound sources. Conventional ESM focuses on relatively low frequencies and cannot provide a satisfactory solution at high frequencies. So its improved method called wideband acoustic holography (WBH) has been proposed, which has high reconstruction accuracy at medium-to-high frequencies. However, it is less accurate for coherent sound sources at low frequencies. To improve the reconstruction accuracy of conventional ESM and WBH, a sound source identification algorithm based on Bayesian compressive sensing (BCS) and ESM is proposed. This method uses a hierarchical Laplace sparse prior probability distribution, and adaptively adjusts the regularization parameter, so that the energy is concentrated near the correct equivalent source. Referring to the function beamforming idea, the original algorithm with order v can improve its dynamic range, and then more accurate position information is obtained. Based on the simulation of irregular microphone array, comparisons with conventional ESM and WBH show that the proposed method is more accurate, suitable for a wider range of frequencies, and has better reconstruction performance for coherent sources. By increasing the order v, the coherent sources can be located accurately. Finally, the stability and reliability of the proposed method are verified by experiments.

An alternating iterative algorithm for sound source identification based on equivalent source method

Near-field acoustical holography (NAH) based on equivalent source method (ESM) is an efficient technique for sound source identification. Conventional ESM with Tikhonov regularization (TRESM), ESM based on CVX MATLAB toolbox (CVX) and wideband acoustic holography (WBH) are commonly used methods for calculating equivalent source strengths. However, all of them have their respective limitations. To address some of these, an alternating iterative algorithm for sound source identification based on equivalent source method (AIESM) is proposed in this article, which is a combination of alternating direction method and a non-monotone line search technique. The method makes use of sparse regularization under the principle of compressive sensing (CS) to calculate equivalent source strengths. Moreover, inspired by the idea of functional beamforming (FB), AIESM with order n can yield an improved dynamic range when detecting the source location. Numerical simulations are carried out at different frequencies, and the results suggest that the computational efficiency of the proposed method is close to that of TRESM. In addition, AIESM has a better reconstruction accuracy than TRESM and WBH in a relatively wide frequency range. Compared with ESM based on CVX, AIESM is slightly better in reconstruction accuracy and has a higher computational efficiency. Meanwhile, AIESM with order n can provide more accurate source position and better resolution. The validity and practicality of the proposed method are further supported by experimental results.