Preprocessing method for assistive listening system - Muhammad Nur Adri, Nawi (2021)
To reduce noise, there a several types of methods available, and the most common practice is using earmuff in industry and hearing aid for people who have hearing loss. With the advancement of technology, noise Cancelling was introduce to various kind of devices, from music to the automotive industry, and this is because, at present, the number of industries greatly increase with the demand for consumers pushing manufacturer to install new equipment or machine to enable them to operate 24 hours. It leads to noise pollution to surrounding neighborhoods to an extent, local voice a complaint. Moreover, Workers needed to the worker for 8 hours straight and endured the noise in the factory. If this continues, it would lead to hearing loss and indeed a very frequent source of sensory impairment in humans. To overcome this Assistive Listening System (ALS) was developed. Unfortunately, the adaptive filter used in ALS currently cannot accept a directly high level of noise. Accepting a high level of noise would lead to the system algorithm being corrupted. The ALS function is to protect workers from a high level of noise that leads to hearing loss. So, the system algorithm is one of the most important parts of the ALS. To overcome this, the filter is needed, and it is well known as a low pass filter (LPF) is a filter that passes signals with frequencies lower than the selected cutoff frequency and attenuates signals higher than the cutoff frequency, and this system needs only lower frequency to enter the system. This project aims to study how to avoid the adaptive filter from corrupted by a high level of noise. Specifically, investigate and suggest 4 low pass filters in the preprocessing stage of ALS. In addition, evaluate the recommended filter in the preprocessing stages of ALS and choose the suitable one. Besides that, research has been made in the literature review to show that the chosen filter has the capability to perform other task and shows it function in other fields. Other than that, this thesis will show the equation on how the filter was made and show the MATLAB code for each filter. As for information, all the filters used in this project are already designed by engineers in MATLAB and used in this project to test the most suitable one for the system. The result may look similar because it is a low pass filter and not the noise cancellation itself. The results show all low pass filters have the potential to be used and protect the system from being corrupted.