Development of a flexible, realistic hearing in noise test environment (R-HINT-E)
| Autor: | Shilpy Gupta, Simon Haykin, Jeff Bondy, Ian C. Bruce, Laurel J. Trainor, Suzanna Becker, Karl Wiklund, Ranil Sonnadara |
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| Rok vydání: | 2004 |
| Předmět: |
Hearing aid
Reverberation Engineering Speech perception business.industry media_common.quotation_subject Speech recognition medicine.medical_treatment Speech processing Control and Systems Engineering Perception QUIET Signal Processing medicine Computer Vision and Pattern Recognition Electrical and Electronic Engineering business Software Digital signal processing Impulse response media_common |
| Zdroj: | Signal Processing. 84:299-309 |
| ISSN: | 0165-1684 |
| DOI: | 10.1016/j.sigpro.2003.10.013 |
| Popis: | Through the use of DSP chips and multiple microphones, hearing aids now offer the possibility of performing signal-to-noise enhancement. Evaluating different algorithms before they are instantiated on a hearing aid is essential. However, commercially available tests of hearing in noise do not allow for speech perception evaluation with a variety of signals, noise types, signal and noise locations, and reverberation. Here we present a flexible realistic hearing in noise testing environment (R-HINT-E) that involves (1) measuring the impulse responses at microphones placed in the ears of a human head and torso model (KEMAR) from many different locations in real rooms of various dimensions and with various reverberation characteristics, (2) creating a corpus of sentences based on the hearing in noise test recorded in quiet from a variety of talkers, (3) creating "soundscapes" representing the input to the ears (or army of microphones in a hearing aid) by convolving specific sentences or noises with the impulse responses for specific locations in a room, and (4) using psychophysical procedures for measuring reception thresholds for speech under a variety of noise conditions. Preliminary evaluation based on the engineering signal-to-error ratio and on human perceptual tests indicates that the convolved sounds closely match real recordings from the same location in the room. R-HINT-E should be invaluable for the evaluation of hearing aid algorithms, as well as more general signal separation algorithms such as independent components analysis. |
| Databáze: | OpenAIRE |
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