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.
