Database of Multichannel In-Ear and Behind-the-Ear Head-Related and Binaural Room Impulse Responses
By H. Kayser, S. Ewert, J. Anemüller, T. Rohdenburg, Volker Hohmann, B. Kollmeier. EURASIP Journal on Advances in Signal Processing, 2009
358 citations recorded by the source corpus.
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.
Subfields: Cognitive Neuroscience, Computational Mechanics, Signal Processing
View Paper: https://www.semanticscholar.org/paper/8516e522783299a14f27f940b00a93c5379cc043
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Citations in the corpus
- A Consolidated Perspective on Multimicrophone Speech Enhancement and Source Separation (2017, neutral): “RWCP [283]9 364 84 7 1 9 no no SiSEC [284]10 ∼50 2 5 1 ∼20 no no AIR [41]11 214 2 8 1 13 no no Binaural RIR [285]12 2920 8 5 1 365 yes yes CAMIL [266]13 32400 2 1 16200 1 yes no CHiME2 [286]14 242 2 1 1 121 yes yes RIRDB [287]15 1872 24 3 3 26 no no”
- Hearing aid Research Data Set for Acoustic Environment Recognition (2020, methodology): “In order to obtain binaural data comparable to our own dummy head recordings, we took the left channel from the stereo music data and, analog to the speech synthesis step further described at the end of this section, convolved it with the HRTFs corredponging to 0◦ from the Kayser database [15].”