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DC Field | Value | Language |
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dc.contributor.author | IBRAHIM, Yakubu | - |
dc.date.accessioned | 2024-05-23T11:16:26Z | - |
dc.date.available | 2024-05-23T11:16:26Z | - |
dc.date.issued | 2017 | - |
dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/1330 | - |
dc.description.abstract | Automatic Speech Recognition has found its application on various aspects of our daily lives such as automatic phone answering service, dictating text and issuing voice commands to computers. Speech recognition is one of the fastest developing fields in the framework of speech science and engineering. Also, in computing technology, it comes as the next major innovation in human computer interaction. However, in speech signal processing, Pre-processing of speech plays a vital role in development of an efficient automatic speech recognition system. Nowadays, Humans are able to interact with computer hardware and other machines through human language. In view of the above, researchers are putting efforts to develop a perfect and efficient speech recognition system but machines are unable to match the performance of human utterances in terms of accuracy of matching and speed of response. Therefore, preprocessing of signal is based on number of applications and drawback of the available techniques of ASR systems. Hence, the process of preprocessing in speech recognition discussed in the study includes: Noise removal, Voice Activity Detection, Pre-emphasis, Framing and Windowing. | en_US |
dc.description.sponsorship | Self | en_US |
dc.language.iso | en | en_US |
dc.publisher | Anale. Seria Informatică | en_US |
dc.relation.ispartofseries | Vol 15; | - |
dc.subject | Automatic Speech Recognition (ASR), | en_US |
dc.subject | Human Computer Interaction (HCI) | en_US |
dc.subject | Pre-processing | en_US |
dc.title | PREPROCESSING TECHNIQUE IN AUTOMATIC SPEECH RECOGNITION FOR HUMAN COMPUTER INTERACTION: AN OVERVIEW | en_US |
dc.type | Article | en_US |
Appears in Collections: | Research Articles |
Files in This Item:
File | Description | Size | Format | |
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15-1-23-IbrahimPaperOnASR_Prepro2017.pdf | 443.59 kB | Adobe PDF | View/Open |
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