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An experiment was conducted to identify the perceptual effects of acoustical properties of domestic listening environments, in a stereophonic reproduction scenario. Nine sound fields, originating from four rooms, were captured and spatially reproduced over a three-dimensional loudspeaker array. A panel of ten expert assessors identified and quantified the perceived differences of those sound fields using their own perceptual attributes. A multivariate analysis revealed two principal dimensions that could summarize the sound fields of this investigation. Four perceptual constructs seem to characterize the sensory properties of these dimensions, relating to Reverberance, Width & Envelopment, Proximity, and Bass. Overall, the results signify the importance of reverberation in residential listening environments on the perceived sensory experience, and as a consequence, the assessors' preferences towards certain decay times. [ABSTRACT FROM AUTHOR]

Abstract: Acoustic feedback is a well-known problem in hearing aids, caused by the undesired acoustic coupling between the hearing aid loudspeaker and microphone. Acoustic feedback produces annoying howling sounds and limits the maximum achievable hearing aid amplification. This paper is focused on adaptive feedback cancellation (AFC) where the goal is to adaptively model the acoustic feedback path and estimate the feedback signal, which is then subtracted from the microphone signal. The main problem in identifying the acoustic feedback path model is the correlation between the near-end signal and the loudspeaker signal caused by the closed signal loop, in particular when the near-end signal is spectrally colored as is the case for a speech signal. This paper adopts a prediction-error method (PEM)-based approach to AFC, which is based on the use of decorrelating prediction error filters (PEFs). We propose a number of improved PEF designs that are inspired by harmonic sinusoidal modeling and pitch prediction of speech signals. The resulting PEM-based AFC algorithms are evaluated in terms of the maximum stable gain (MSG), filter misadjustment, and computational complexity. Simulation results for a hearing aid scenario indicate an improvement up to 5–7dB in MSG and up to 6–8dB in terms of filter misadjustment. [Copyright &y& Elsevier]

Abstract: Noise reduction (NR) and dynamic range compression (DRC) are basic components in hearing aids, but generally these components are developed and evaluated independently of each other. Hearing aids typically use a serial concatenation of NR and DRC. However, the DRC in such a concatenation negatively affects the performance of the NR stage: the residual noise after NR receives more amplification compared to the speech, resulting in a signal-to-noise-ratio (SNR) degradation. The integration of NR and DRC has not received a lot of attention so far. In this paper, a multi-channel Wiener filter (MWF)-based approach is presented for speech and noise scenarios, where an MWF-based NR algorithm is combined with DRC. The proposed solution is based on modifying the MWF and the DRC to incorporate the conditional speech presence probability in order to avoid residual noise amplification. The goal is then to analyse any undesired interaction effects by means of objective measures. Experimental results indeed confirm that a serial concatenation of NR and DRC degrades the SNR improvement provided by the NR, whereas the combined approach proposed here shows less degradation of the SNR improvement at a low increase in distortion compared to a serial concatenation. [Copyright &y& Elsevier]

Abstract: This paper analyses the output signal-to-noise ratio for a standard noise reduction scheme based on the multichannel Wiener filter and for an integrated active noise control and noise reduction scheme based on the filtered-X multichannel Wiener filter, both applied in a hearing aid framework that includes the effects of signal leakage through an open fitting and secondary path effects. In previous work, integrating noise reduction and active noise control has been shown to allow to compensate for effects of signal leakage and secondary path effects. These experimental results are now verified theoretically. The output signal-to-noise ratios are derived under a single speech source scenario. Theoretical results are then compared to simulations for a single noise source scenario and a multiple noise sources scenario. [Copyright &y& Elsevier]

Abstract: In this paper, we formulate the multi-pitch estimation problem and propose a number of methods to estimate the set of fundamental frequencies. The proposed methods, based on the nonlinear least-squares (NLS), MUltiple SIgnal Classification (MUSIC) and the Capon principles, estimate the multiple fundamental frequencies via a number of one-dimensional searches. We also propose an iterative method based on the Expectation Maximization (EM) algorithm. The statistical properties of the methods are evaluated via Monte Carlo simulations for both the single- and multi-pitch cases. [Copyright &y& Elsevier]