Improved Sound Classification by Means of Sound Localization in Hearing Devices
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Date
2020
Publication Type
Doctoral Thesis
ETH Bibliography
yes
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Abstract
Hearing devices are becoming a more and more common solution for
people with mild to profound hearing loss. The hearing instruments are,
indeed, able to compensate for the individual hearing loss while trying
to provide the best hearing experience possible. However, the acoustic
environments which the average user experiences during the day are
usually very different and complex. Most of the devices try to cope with
these big variations in the surroundings by adjusting the settings based
on some parameters senses by the microphones. One of the most common
solutions, in this regards, is the sound classifier. The main objective
of this tool is to blindly understand the acoustic scenario around the
hearing aid user and enable the appropriate change in the settings based
on the detected environment. Although the sound classifier is a precious
tool in a hearing device, very often it does not consider a very important
aspect of sound, i.e., sound is generated by sources placed in a 3D world.
The spatial components in the acoustic scenarios are often discarded
after being sensed by the microphones. In this work, a possible solution
to integrate spatial components to the sound classifier in order to have a
better understanding of the acoustic environment was investigated. The
solution here proposed is to extend the inputs of the sound classifier
with additional informations about the location of the sound sources
present in the environment. To provide these additional informations, a
localization algorithm tailored for hearing devices applications has been
developed. The algorithm creation was inspired by the human auditory
system which relies on the estimation of the binaural cues. In addition
to the localization algorithm, a blind direct-to-reverberant energy ratio
for speech signal has been developed. Moreover, an exploratory solution
for head tracking based on a 3-axis accelerometer was investigated.
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published
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Contributors
Examiner : Loeliger, Hans-Andrea
Examiner : Kompis, Martin
Examiner : Dillier, Norbert
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Journal / series
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Pages / Article No.
Publisher
ETH Zurich
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Edition / version
Methods
Software
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Date collected
Date created
Subject
sound localization; binaural cues; sound classification; directional classifier; Beamformer; DRR estimation; head-tracker; hearing devices
Organisational unit
03568 - Loeliger, Hans-Andrea / Loeliger, Hans-Andrea