Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/26404
Full metadata record
DC FieldValueLanguage
dc.contributor.authorAhmad M.R.-
dc.contributor.authorZaid A.F.A.M.-
dc.contributor.authorBakar M.H.A.-
dc.contributor.authorAlias M.F.-
dc.contributor.authorKrishnan P., UniKL MSI-
dc.date.accessioned2022-12-06T01:29:59Z-
dc.date.available2022-12-06T01:29:59Z-
dc.date.issued2022-12-06-
dc.identifier.urihttp://hdl.handle.net/123456789/26404-
dc.description.abstractSpeech recognition technology is one of the quickly developing advanced technologies of engineering. It has various applications in different zones and offers potential points of interest. There is a correlation to pre-requirement for speech recognition and machine learning which is that grammar classification and a method for extraction phonemes from utterances are required. For Speech architecture, three models are utilized in speech recognition to do the preparing like a phonetic dictionary, acoustic model, language model. There are four stages of the recognition process: analysis, feature extraction, modeling and matching. Deficiency factors were brought forward which is the dataset threshold and feature extracting method. The higher dataset produces a lower word error rate (WER) which gives more accuracy in the recognition process.en_US
dc.language.isoenen_US
dc.titleGPU Accelerated Speech Recognitionen_US
dc.typeBook chapteren_US
dc.conference.nameAdvanced Structures Materials, Volume 148, 2021en_US
dc.conference.year2021en_US
Appears in Collections:Journal Articles

Files in This Item:
File Description SizeFormat 
GPU Accelerated Speech Recognition.pdf51.99 kBAdobe PDFView/Open


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