Hanum, H.M. and Aziz, A.S. and Bakar, Z.A. and Diah, N.M. and Ahmad, W.F.W. and Ali, N.M. (2021) Melody Training for Quranic Tarannum. In: UNSPECIFIED.
Full text not available from this repository.Abstract
There is a lack of application that promotes melody training despite research in speech-related applications. Melody training technology allows users to do repetitive practice and provide feedback on the user's performance. Conventional melody training requires one to have face-to-face training to master the melody from a teacher. The study focuses on people who want to learn Tarannum as a preliminary step for mastering the melodic patterns for a Tarannum. The proposed application implements a curve similarity algorithm to help the user to train their Quranic recitations, following the melody of the Tarannum. The curve similarity algorithm captures the pattern of melodic recitations and provides feedback to the user. The application compares the recorded Taranum melody with the trained patterns of the Bayati recitations and provides feedback on the accuracy, which is measured using a melody curve similarity algorithm. The application offers an experience and nurtures users to repeat recitations aiming for the highest possible accuracy. The research can achieve the highest accuracy on some segments at 100 similarity with overall accuracy at 88.7 by verse. For example, the users will do their best to get a passing grade for every training. Hence, the user will keep trying until they achieve their desired result and learn the Tarannum melody. © 2021 IEEE.
Item Type: | Conference or Workshop Item (UNSPECIFIED) |
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Additional Information: | cited By 2; Conference of 5th International Conference on Information Retrieval and Knowledge Management, CAMP 2021 ; Conference Date: 15 June 2021 Through 16 June 2021; Conference Code:171213 |
Uncontrolled Keywords: | Information retrieval; Knowledge management; Personnel training, Curve similarities; Face to face; Overall accuracies, User experience |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 10 Nov 2023 03:29 |
Last Modified: | 10 Nov 2023 03:29 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/14821 |