Please use this identifier to cite or link to this item:
http://hdl.handle.net/123456789/26404
Title: | GPU Accelerated Speech Recognition |
Authors: | Ahmad M.R. Zaid A.F.A.M. Bakar M.H.A. Alias M.F. Krishnan P., UniKL MSI |
Issue Date: | 6-Dec-2022 |
Abstract: | Speech 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. |
URI: | http://hdl.handle.net/123456789/26404 |
Appears in Collections: | Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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GPU Accelerated Speech Recognition.pdf | 51.99 kB | Adobe PDF | View/Open |
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