Implications of Adaptive Acoustic Augmentation in Real-Time using Machine Learning for Hearing Devices

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dc.contributor.authorBalasubramanyam, Abhilash Kashyap
dc.date.accessioned2024-10-24T09:07:59Z
dc.date.available2024-10-24T09:07:59Z
dc.date.submitted2021-05-06
dc.description.abstractPurpose. 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.
dc.description.tableofcontents1 Introduction 1.1 Research Objectives 1.2 Value and Target Audience 1.3 Scope and Constraints 1.4 Structure of the Document 2 Literature Review 2.1 Sound 2.2 Noise 2.3 Noise Cancellation 2.4 Products Aiding to Purify Audio by Technological Implementation 3 Research Design 3.1 Methodology 3.2 Methods 3.3 Population and Sampling 3.4 Analysis 3.5 Validity and Reliability 3.6 Methodological Constraints 3.7 Ethical Considerations 4 Results & Discussion 4.1 Preprocessed Data 4.2 Postprocessed Data 4.3 Other Derived Data 4.4 Interpretation 4.5 Synopsis 5 Conclusion 5.1 Limitations 5.2 Recommendations for Future Research
dc.identifier.urihttps://repository.iu.org/handle/123456789/4039
dc.language.isoen
dc.publisherIU International University of Applied Sciences
dc.subjectIU Campus Studies
dc.subjectMaster Thesis
dc.subjectBig Data Management
dc.subjectMachine Learning
dc.subjectHearing Devices
dc.subjectAdaptive Noise Cancellation
dc.subjectNoise
dc.subjectAuditory Governmental Regulations
dc.titleImplications of Adaptive Acoustic Augmentation in Real-Time using Machine Learning for Hearing Devices
dc.typeMaster Thesis
dcterms.extent91
iu.studyprogrammeBig Data Management

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