Arabic Speech Recognition for Quranic Words: Building an Audio Dictionary

Document Type : Original Article

Authors

1 Systems and Biomedical Engineering Department, Faculty of Engineering, Cairo University, Giza, Egypt.

2 Information Technology & Computer Science, Nile University, Giza, Egypt.

3 Systems and Biomedical Engineering Department, Faculty of Engineering, El-Shorouk Academy, Cairo, Egypt.

Abstract

This paper presents the development and implementation of an Automatic Speech Recognition (ASR)-based Audio Dictionary Database for Quranic words, integrating modern speech processing and recognition techniques. The system utilizes speech feature extraction, pattern recognition, and audio matching to detect and log Quranic words from recitations. A computational approach extracts all 19,058 unique dictionary words from the Quranic text, and a dedicated speech processing application has been developed to detect these words in Quranic recitations. The application employs enhanced speech pattern-matching techniques, successfully identifying all dictionary words in Chapter 30 (1,272 words) and spotting 22 Quranic words across the entire Quran in 373 occurrences, achieving 95% accuracy. The Audio Dictionary of Quranic Words is a novel contribution that addresses the shortage of publicly available datasets for researchers. This dataset can be used to support Tajweed instruction, advance Arabic speech technology, and serve as a valuable resource for linguistic research, ASR development, and speech-based AI applications.

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