Aravinda, K. PSandeepa, K. G. HSedara, V. VChamodya, A. K. Y. LDharmasena, TAbeygunawardhana, P. K. W2022-02-142022-02-142021-12-09A. K. P., S. K. G. H., S. V. V., C. A. K. Y. L., T. Dharmasena and P. K. W. Abeygunawardhana, "Digital Preservation and Noise Reduction using Machine Learning," 2021 3rd International Conference on Advancements in Computing (ICAC), 2021, pp. 181-186, doi: 10.1109/ICAC54203.2021.9671137.978-1-6654-0862-2https://rda.sliit.lk/handle/123456789/1142This paper proposes a digital preservation solution for Sinhala audios to conserve those as documents with noise reduction. The solution has implemented multiple noise reduction techniques as a pre-processing step to remove unwanted internal and external noises. A two-step, two-way noise reduction process is applied to produce clean audios based on Deep Convolutional Neural Network (DCNN) and adaptive filter-based techniques. This approach implements two separate noise reduction models for internal and external noises. After that, the speech recognition decoder recognizes the speech and converts it to a Unicode document by acoustic, language, and pronunciation models using extracted audio features from the denoised audio. Further, noise reduction models are decoupled from the preservation solution and exposed as a sub solution for multilingualism noise reduction, supporting English and Sinhala audios.enDigital PreservationNoise ReductionMachine LearningInternal and External NoiseArticle10.1109/ICAC54203.2021.9671137