Active noise control (ANC) is an active noise mitigation method that has in recent years become increasingly prevalent. The method relies on the principle of superposition, canceling unwanted noise through the addition of a second sound wave with the same amplitude but an inverted phase to the first. One of the most common applications of ANC is in hearables, particularly in wireless earbuds. Because of individual differences in ear anatomy, the requirements for an effective ANC system will vary slightly among different users. However, the static nature of most ANC systems in hearables means that they are unable to account for these anatomical differences, resulting in inconsistent noise reduction across individuals. The aim of this project is to develop an adaptive ANC system capable of accounting for individual variations in ear anatomy through the use of optimization algorithms and adaptive filters. The proposed adaptive ANC system is designed to operate as a separate layer alongside the static ANC system and is implemented in a simulated environment with the help of Python. The effectiveness of the adaptive system is evaluated relative to the static system in terms of overall sound pressure level (OASPL) as well as power spectral density (PSD) across several test participants. The results indicate that the adaptive system indeed provides a noticeable improvement over the standalone static system.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-532303 |
| Date | January 2024 |
| Creators | Sun, Martin |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | MATVET-F ; 24033 |
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