Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1063
Full metadata record
DC FieldValueLanguage
dc.contributor.authorAravinda, K.P.-
dc.contributor.authorSandeepa, K.G.H.-
dc.contributor.authorSedara, V. V.-
dc.contributor.authorChamodya, A.K.Y.L.-
dc.contributor.authorDharmasena, T.-
dc.contributor.authorAbeygunawardhana, P.K.W.-
dc.date.accessioned2022-02-09T08:13:36Z-
dc.date.available2022-02-09T08:13:36Z-
dc.date.issued2021-12-09-
dc.identifier.issn978-1-6654-0862-2/21-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/1063-
dc.description.abstractThis 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.en_US
dc.language.isoenen_US
dc.publisher2021 3rd International Conference on Advancements in Computing (ICAC), SLIITen_US
dc.subjectNoise Reductionen_US
dc.subjectInternal and External Noisesen_US
dc.subjectSpeech Recognitionen_US
dc.titleDigital Preservation and Noise Reduction using Machine Learningen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICAC54203.2021.9671137en_US
Appears in Collections:3rd International Conference on Advancements in Computing (ICAC) | 2021
Department of Computer systems Engineering-Scopes
Research Papers - Dept of Computer Systems Engineering

Files in This Item:
File Description SizeFormat 
Digital_Preservation_and_Noise_Reduction_using_Machine_Learning.pdf
  Until 2050-12-31
1.93 MBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.