The Influence of Speech Recognition Software on English Pronunciation Improvement: A Quasi-Experimental Investigation

Proper pronunciation is an important aspect of learning English, yet often a challenge for second language learners. Speech recognition-based technology offers an innovative solution to improve pronunciation skills through instant feedback. This study aims to evaluate the effect of speech recognition software on improving English pronunciation skills in English Language Education students at Sultan Agung Islamic University. Using a quasi-experimental design with pre-test and post-test, the study involved two groups: an experimental group that used speech recognition software and a control group that followed conventional teaching. The results showed that the experimental group experienced significant improvements in pronunciation skills, including phonemes (44.8%), intonation (45.7%), and word stress (33.4%), while the control group showed smaller improvements. Statistical analysis using paired t-test and independent t-test confirmed that the difference between the two groups was highly significant (p-value < 0.05). The findings indicate that speech recognition software can improve English pronunciation skills more effectively than conventional methods. This study contributes to the development of the use of technology in English language education, particularly in improving pronunciation through instant feedback. The practical implications of this study include the potential integration of this tool in the English language learning curriculum to increase students' independence in practicing pronunciation.

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Publication Details

Journal
Jurnal Multidisiplin Dehasen (MUDE)
Published
2025-07-12
DOI
https://doi.org/10.37676/mude.v4i3.8409
Primary Topic
Speech and dialogue systems
Type
article
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article

The Influence of Speech Recognition Software on English Pronunciation Improvement: A Quasi-Experimental Investigation

Ahmad Lizamuddin, Mohammad Noor Zuhri
Jurnal Multidisiplin Dehasen (MUDE)
Speech and dialogue systems
article

The Influence of Speech Recognition Software on English Pronunciation Improvement: A Quasi-Experimental Investigation

Ahmad Lizamuddin, Mohammad Noor Zuhri
article en

Abstract

Proper pronunciation is an important aspect of learning English, yet often a challenge for second language learners. Speech recognition-based technology offers an innovative solution to improve pronunciation skills through instant feedback. This study aims to evaluate the effect of speech recognition software on improving English pronunciation skills in English Language Education students at Sultan Agung Islamic University. Using a quasi-experimental design with pre-test and post-test, the study involved two groups: an experimental group that used speech recognition software and a control group that followed conventional teaching. The results showed that the experimental group experienced significant improvements in pronunciation skills, including phonemes (44.8%), intonation (45.7%), and word stress (33.4%), while the control group showed smaller improvements. Statistical analysis using paired t-test and independent t-test confirmed that the difference between the two groups was highly significant (p-value < 0.05). The findings indicate that speech recognition software can improve English pronunciation skills more effectively than conventional methods. This study contributes to the development of the use of technology in English language education, particularly in improving pronunciation through instant feedback. The practical implications of this study include the potential integration of this tool in the English language learning curriculum to increase students' independence in practicing pronunciation.

Jurnal Multidisiplin Dehasen (MUDE)Vol. 4(3)
Sultan Agung Islamic University (ID)
Openalex Percentile: Top 89%
Speech and dialogue systems
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The Influence of Speech Recognition Software on English Pronunciation Improvement: A Quasi-Experimental Investigation — Ahmad Lizamuddin, Mohammad Noor Zuhri · Jurnal Multidisiplin Dehasen (MUDE) (2025) | TGRS Research Map | TGRS