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http://hdl.handle.net/123456789/26404Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Ahmad M.R. | - |
| dc.contributor.author | Zaid A.F.A.M. | - |
| dc.contributor.author | Bakar M.H.A. | - |
| dc.contributor.author | Alias M.F. | - |
| dc.contributor.author | Krishnan P., UniKL MSI | - |
| dc.date.accessioned | 2022-12-06T01:29:59Z | - |
| dc.date.available | 2022-12-06T01:29:59Z | - |
| dc.date.issued | 2022-12-06 | - |
| dc.identifier.uri | http://hdl.handle.net/123456789/26404 | - |
| dc.description.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. | en_US |
| dc.language.iso | en | en_US |
| dc.title | GPU Accelerated Speech Recognition | en_US |
| dc.type | Book chapter | en_US |
| dc.conference.name | Advanced Structures Materials, Volume 148, 2021 | en_US |
| dc.conference.year | 2021 | en_US |
| Appears in Collections: | Journal Articles | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| GPU Accelerated Speech Recognition.pdf | 51.99 kB | Adobe PDF | View/Open |
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