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Noise reduction is a crucial aspect of hearing aids, which researchers havebeen striving to address over the years. However, most existing noise reductionalgorithms have primarily been evaluated using English. Considering thelinguistic differences between English and Sinhala languages, includingvariation in syllable structures and vowel duration, it is very important toassess the performance of noise reduction tailored to the Sinhala language.This paper presents a comprehensive analysis between wavelet transformation andadaptive filters for noise reduction in Sinhala languages. We investigate theperformance of ten wavelet families with soft and hard thresholding methodsagainst adaptive filters with Normalized Least Mean Square, Least Mean SquareAverage Normalized Least Mean Square, Recursive Least Square, and AdaptiveFiltering Averaging optimization algorithms along with cepstral andenergy-based voice activity detection algorithms. The performance evaluation isdone using objective metrics; Signal to Noise Ratio (SNR) and PerceptualEvaluation of Speech Quality (PESQ) and a subjective metric; Mean Opinion Score(MOS). A newly recorded Sinhala language audio dataset and the NOIZEUS databaseby the University of Texas, Dallas were used for the evaluation. Our code isavailable athttps://github.com/ChathukiKet/Evaluation-of-Noise-Reduction-Methods

Evaluation of Noise Reduction Methods for Sentence Recognition by Sinhala Speaking Listeners