Implications of Adaptive Acoustic Augmentation in Real-Time using Machine Learning for Hearing Devices
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IU International University of Applied Sciences
Abstract
Purpose. This thesis focusses mainly on the noise and its delimitations to communication
and its effects on the auditory cognition. The misuse or underutilization of
this auditory system is equivalent to discard a bestowed gift. The mischief of noise
is thus in need to be explored.
Value. The results of this thesis help to understand the areas of interest to either
channelize noise to the benefit of the user or to curtail the existence of the same. The
occupation of noise in everyday life is also highly disregarded to a certain degree
by either being used to its presence or general helplessness. This thesis brings a
spotlight over the said areas to focus better over the needs of the user.
Methods. This thesis is largely dependent on the population’s prorogation of their
perception towards noise. Thus, a post-positivist approach is chosen at first and the
evidence documented from that is validated through the minor approach from the
interpretivist approach. To facilitate the same, a mass population data gathering
from across the globe survey was conducted with responses that are not limited to
any age or geographical distribution. This thereby helps in converging from a large
sample of data to individualistic inferences.
Key findings. The pivotal observation was the perception of an entity disregarded
to be unimportant and of no value was rather very keenly accepted by certain
groups of people. The acceptance criteria and the need for improvement in certain
areas were very clearly identified.
Conclusion. Noise is still an undesirable factor to audio propagation. However, this
quality cannot be eliminated from various constraints. Nevertheless, it can be understood
better by probing over the varying levels of its perceptibility by the scattered
population with unique beliefs and tolerances. Noise also cannot be generalized
to audio in general when working towards corrective measures, besides it must
be identified to the type of audio propagation involved.
Keywords: noise, audio communication, hands-free devices, auditory governmental
regulations, adaptive noise cancellation.
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Keywords
IU Campus Studies, Master Thesis, Big Data Management, Machine Learning, Hearing Devices, Adaptive Noise Cancellation, Noise, Auditory Governmental Regulations