Abstract
An eight-channel database of head-related impulse responses (HRIRs) and binaural room impulse responses (BRIRs) is introduced. The impulse responses (IRs) were measured with three-channel behind-the-ear (BTEs) hearing aids and an in-ear microphone at both ears of a human head and torso simulator. The database aims at providing a tool for the evaluation of multichannel hearing aid algorithms in hearing aid research. In addition to the HRIRs derived from measurements in an anechoic chamber, sets of BRIRs for multiple, realistic head and sound-source positions in four natural environments reflecting daily-life communication situations with different reverberation times are provided. For comparison, analytically derived IRs for a rigid acoustic sphere were computed at the multichannel microphone positions of the BTEs and differences to real HRIRs were examined. The scenes' natural acoustic background was also recorded in each of the real-world environments for all eight channels. Overall, the present database allows for a realistic construction of simulated sound fields for hearing instrument research and, consequently, for a realistic evaluation of hearing instrument algorithms.
Highlights
Performance evaluation is an important part of hearing instrument algorithm research since only a careful evaluation of accomplished effects can identify truly promising and successful signal enhancement methods
As evaluation of the quality, the signal-to-noise ratio (SNR) of the measured impulse responses was calculated for each environment
The average noise power was estimated from the noise floor irnoise(t) for the interval Tend at end of the measured impulse responses (IRs), where the IR has declined below the noise level
Summary
Performance evaluation is an important part of hearing instrument algorithm research since only a careful evaluation of accomplished effects can identify truly promising and successful signal enhancement methods. The gold standard for evaluation will always be the unconstrained real-world environment, which comes at a relatively high cost in terms of time and effort for performance comparisons. Simulation approaches to the evaluation task are the first steps in identifying good signal processing algorithms. It is important to utilize simulated input signals that represent real-world signals as faithfully as possible, especially if multimicrophone arrays and binaural hearing instrument algorithms are considered that expect input from both sides of a listener’s head. The simplest approach to model the input signals to a multichannel or binaural hearing instrument is the free-field model. More elaborate models are based on analytical formulations of the effect that a rigid sphere has on the acoustic field [1, 2]
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