Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1008
Title: Digital Preservation and Noise Reduction using Machine Learning
Authors: Aravinda, K.P.
Sandeepa, K.G.H.
Sedara, V. V.
Chamodya, A.K.Y.L.
Dharmasena, T.
Abeygunawardhana, P.K.W.
Keywords: Noise Reduction
Internal and External Noises
Speech Recognition
Issue Date: 9-Dec-2021
Publisher: 2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT
Abstract: This 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.
URI: http://rda.sliit.lk/handle/123456789/1008
ISSN: 978-1-6654-0862-2/21
Appears in Collections:3rd International Conference on Advancements in Computing (ICAC) | 2021
Research Papers - Dept of Computer Systems Engineering
Research Papers - IEEE

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