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Afan Oromo Speech-Based Computer Command and Control: An Evaluation with Selected Commands

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dc.contributor.author Teshite, Kebede
dc.contributor.author Mamo, Getachew
dc.contributor.author Calpotura, Kris
dc.date.accessioned 2025-03-20T10:54:06Z
dc.date.available 2025-03-20T10:54:06Z
dc.date.issued 2023-10
dc.identifier.uri https://doi.org/10.1155/2023/9959015
dc.identifier.uri https://repository.ju.edu.et//handle/123456789/9404
dc.description.abstract Speech-based computer command and control utilize natural speech to enable computers to understand human language and execute tasks through commands. However, there has been no study or development of a speech-based command and control system for Microsoft Word in Afan Oromo. Te primary aim of this research is to investigate and develop a speech-based command and control system for Afan Oromo using a selected set of command-and-control words from MS Word. To ac complish this objective, a speech recognizer was developed using the HTK toolkit, employing a small vocabulary, isolated words, speaker independence, and HMM-based techniques. Te translation of the selected MS command words from English to Afan Oromo was completed in order to develop this automatic speech-based computer command system. Audio recordings were obtained from 38 speakers (16 females and 22 males) aged between 18 and 40years, based on their availability. Word-level speech recognition was performed using MFCC and data processing, which are widely used and are efective approaches in speech recognition. Out of a total of 64MS command words, 54 words (84.37%) were used for training and 10 words (15.63%) were used for testing. Live and nonlive evaluation techniques were employed to assess the performance of the recognizer. Te live recognizer, which considers variations in the environment, outperformed the nonlive recognizer due to the infuence of neighboring phones. Te performance results for the monophone tied state, triphone, and triphone-based recognizers were 78.12%, 86.87%, and 88.99%, respectively. Tus, the triphone-based recognizer exhibited the best performance among the nonlive recognizers. Te challenges of limited resources in this research study were limited to investigate speech-based commands for computers using only selected MS commands, which play a crucial role in text processing. In order to evaluate a speech-based interface in a real environment, there were no components available for object-as-a-service. Te experimental fndings of this study demonstrated that if an adequate amount of language resources was available, a computer-based Afan Oromo speech-based interface for command-and-control purposes could be developed. en_US
dc.language.iso en en_US
dc.publisher Hindawi en_US
dc.subject Afan Oromo en_US
dc.subject MFCC en_US
dc.subject HTK en_US
dc.subject Commands en_US
dc.title Afan Oromo Speech-Based Computer Command and Control: An Evaluation with Selected Commands en_US
dc.type Article en_US


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