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Article
Peer-Review Record

Rule-Based Embedded HMMs Phoneme Classification to Improve Qur’anic Recitation Recognition

Electronics 2023, 12(1), 176; https://doi.org/10.3390/electronics12010176
by Ammar Mohammed Ali Alqadasi 1, Mohd Shahrizal Sunar 2,3,*, Sherzod Turaev 4,*, Rawad Abdulghafor 1,*, Md Sah Hj Salam 2, Abdulaziz Ali Saleh Alashbi 2, Ali Ahmed Salem 5 and Mohammed A. H. Ali 6
Reviewer 1:
Reviewer 2:
Reviewer 3: Anonymous
Electronics 2023, 12(1), 176; https://doi.org/10.3390/electronics12010176
Submission received: 30 November 2022 / Revised: 21 December 2022 / Accepted: 22 December 2022 / Published: 30 December 2022
(This article belongs to the Special Issue Signal and Image Processing Applications in Artificial Intelligence)

Round 1

Reviewer 1 Report

This paper has a high thematic relevance since it carries out an exhaustive analysis. However some recommendations must be followed:

- the introduction section must present the objectives of the study, a major finding, and the structure of the article.

- between the following sub-sections: 3.1. and 3.1.1. must include a transition paragraph; for 3.3 and 3.3.1. as well;

For the final section, number 5, you must address better the aim of the study, the objectives (if they were achieved or not), and the implications (theoretical and managerial).

Also, some references must be revised due to the setup;  I have observed some errors.

I wish you good work!

Author Response

The authors would like to thank the Reviewer for his comments. The reviewer’s comments were taken into account and all the changes were marked in yellow in the revised manuscript. 
Kindly see the attachments

Author Response File: Author Response.pdf

Reviewer 2 Report

This paper targets phoneme classification algorithms, especially for the Islamic language, which is very practical and interesting. The Rule-Based Phoneme Duration Algorithm to improve phoneme classification is proposed and tested with high accuracy. The overall quality of this research is good. I have no further comments on this manuscript.

Author Response

The authors would like to thank the Reviewer for his comments.

Reviewer 3 Report

This article presents a rule-based phoneme duration algorithm to improve phoneme classification in Quranic recitation. The proposed algorithm achieved outstanding accuracy, ranging from 99.87% to 100% depending on the Medd type. The results obtained from the proposed algorithm will contribute significantly to the recognition models of Qur'anic recitations.

The study is well planned. The base is adequate, the methodological design successful. The results come close to effectively reflecting the findings of the study. The conclusions respond to the proposed objectives and with current references. Its publication is recommended given the aforementioned conditions and the interest of the topic. For all the above, I consider that this work can be published.

Thank you

Author Response

The authors would like to thank the Reviewer for his comments.

Round 2

Reviewer 1 Report

Good work!

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