Spatially selective active noise control systems.

Active noise control (ANC) systems are commonly designed to achieve maximal sound reduction regardless of the incident direction of the sound. When desired sound is present, the state-of-the-art methods add a separate system to reconstruct it. This can result in distortion and latency. In this work, we propose a multi-channel ANC system that only reduces sound from undesired directions, and the system truly preserves the desired sound instead of reproducing it. The proposed algorithm imposes a spatial constraint on the hybrid ANC cost function to achieve spatial selectivity. Based on a six-channel microphone array on a pair of augmented eyeglasses, results show that the system minimized only noise coming from undesired directions. The control performance could be maintained even when the array was heavily perturbed. The proposed algorithm was also compared with the existing methods in the literature. Not only did the proposed system provide better noise reduction, but it also required much less effort. The binaural localization cues did not need to be reconstructed since the system preserved the physical sound wave from the desired source.

Preliminary Examination of the Accuracy of a Fall Detection Device Embedded into Hearing Instruments.

BACKGROUND: Accidental falls are a significant health risk to older adults and patients seen in audiology clinics. Personal emergency response systems are effective in preventing long lies (defined as remaining on the floor or ground for greater than one hour after a fall), but some individuals would prefer to wear less-conspicuous devices than a traditional neck-worn pendant. No previous investigation has compared the accuracy of head-worn fall detection devices with those worn on other parts of the body. In this study, we compared the accuracy of one commonly used fall detection pendant with two variants of a new hearing instrument-based fall detection system. PURPOSE: The purpose of the study was to evaluate the accuracy of detecting falls by using inertial sensors embedded in hearing instruments. RESEARCH DESIGN: A study with repeated measures for one group. STUDY SAMPLE: Ten young adults served as participants. All participants had normal or corrected-to-normal vision during testing. Individuals were excluded if they had self-reported cardiac disorders, recent concussions, or musculoskeletal conditions. DATA COLLECTION AND ANALYSIS: Data were collected from inertial measurement unit (IMU) sensors, embedded into a binaural set of hearing instruments, during laboratory-based simulations of falls, near-falls, and activities of daily living (ADLs). The detection state of a fall detection pendant was simultaneously recorded during performance of each trial and compared with the outputs of offline hearing instrument firmware emulators. RESULTS: One hearing instrument-based fall detection system was more accurate than the fall detection pendant. A second hearing instrument-based fall detection system performed similar to the fall detection pendant. Each of the three fall detection systems investigated were robust against false-positive detections during ADLs. CONCLUSIONS: Preliminary findings demonstrate that hearing instruments embedded with a fall detection device (FDD) may be a suitable alternative to more traditional forms of FDDs (e.g., pendant, wrist-worn device, etc.) for detecting falls and potentially preventing long lies.

Monaural Speech Dereverberation Using Temporal Convolutional Networks with Self Attention.

In daily listening environments, human speech is often degraded by room reverberation, especially under highly reverberant conditions. Such degradation poses a challenge for many speech processing systems, where the performance becomes much worse than in anechoic environments. To combat the effect of reverberation, we propose a monaural (single-channel) speech dereverberation algorithm using temporal convolutional networks with self attention. Specifically, the proposed system includes a self-attention module to produce dynamic representations given input features, a temporal convolutional network to learn a nonlinear mapping from such representations to the magnitude spectrum of anechoic speech, and a one-dimensional (1-D) convolution module to smooth the enhanced magnitude among adjacent frames. Systematic evaluations demonstrate that the proposed algorithm improves objective metrics of speech quality in a wide range of reverberant conditions. In addition, it generalizes well to untrained reverberation times, room sizes, measured room impulse responses, real-world recorded noisy-reverberant speech, and different speakers.

Effects of reverberation and noise on speech intelligibility in normal-hearing and aided hearing-impaired listeners.

Many hearing-aid wearers have difficulties understanding speech in reverberant noisy environments. This study evaluated the effects of reverberation and noise on speech recognition in normal-hearing listeners and hearing-impaired listeners wearing hearing aids. Sixteen typical acoustic scenes with different amounts of reverberation and various types of noise maskers were simulated using a loudspeaker array in an anechoic chamber. Results showed that, across all listening conditions, speech intelligibility of aided hearing-impaired listeners was poorer than normal-hearing counterparts. Once corrected for ceiling effects, the differences in the effects of reverberation on speech intelligibility between the two groups were much smaller. This suggests that, at least, part of the difference in susceptibility to reverberation between normal-hearing and hearing-impaired listeners was due to ceiling effects. Across both groups, a complex interaction between the noise characteristics and reverberation was observed on the speech intelligibility scores. Further fine-grained analyses of the perception of consonants showed that, for both listener groups, final consonants were more susceptible to reverberation than initial consonants. However, differences in the perception of specific consonant features were observed between the groups.

Generalized acoustic energy density based active noise control in single frequency diffuse sound fields.

In a diffuse sound field, prior research has established that a secondary source can theoretically achieve perfect cancellation at an error microphone in the far field of the secondary source. However, the sound pressure level is generally only reduced in a small zone around the error sensor, and at a distance half of a wavelength away from the error sensor, the averaged sound pressure level will be increased by more than 10 dB. Recently an acoustic energy quantity, referred to as the generalized acoustic energy density (GED), has been introduced. The GED is obtained by using a weighting factor in the formulation of total acoustic energy density. Different values of the weighting factor can be chosen for different applications. When minimizing the GED at the error sensor, one can adjust the weighting factor to increase the spatial extent of the "quiet zone" and to achieve a desired balance between the degree of attenuation in the quiet zone and the total energy added into the sound field.

Generalized acoustic energy density.

The properties of acoustic kinetic energy density and total energy density of sound fields in lightly damped enclosures have been explored thoroughly in the literature. Their increased spatial uniformity makes them more favorable measurement quantities for various applications than acoustic potential energy density (or squared pressure), which is most often used. In this paper, a generalized acoustic energy density (GED), will be introduced. It is defined by introducing weighting factors into the formulation of total acoustic energy density. With an additional degree of freedom, the GED can conform to the traditional acoustic energy density quantities, or it can be optimized for different applications. The properties of the GED will be explored in this paper for individual room modes, a diffuse sound field, and a sound field below the Schroeder frequency.

A hybrid modal analysis for enclosed sound fields.

A hybrid modal expansion that combines the free field Green's function and a modal expansion will be presented in this paper based on a review and an extension of the existing modal analysis theories for the sound field in enclosures. The enclosed sound field will be separated into the direct field and reverberant field, which have been treated together in the traditional modal analysis. Studies on a point source in rectangular enclosures show that the hybrid modal expansion converges notably faster than the traditional modal expansions, especially in the region near the source, and introduces much smaller errors with a limited number of modes. The hybrid modal expansion can be easily applied to complex sound sources if the free field responses of the sources are known. Damped boundaries are also considered in this paper, and a set of modified modal functions is introduced, which is shown to be suitable for many damped boundary conditions.