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Thank you for addressing the final round of minor revisions. In light of the reviewer's positive reassessment and my own check of the new revision, I'm happy to recommend the paper for acceptance.
[# PeerJ Staff Note - this decision was reviewed and approved by Xiangjie Kong, a PeerJ Section Editor covering this Section #]
This is a revised version of the initial submission. As a reviewer of this manuscript, I have raised various questions in the first round that are properly addressed by the authors. I appreciate the efforts of the authors. I have no further comments on this submission. My recommendation is to accept the paper in its current version. Thank you
Yes
Yes
NA
Please address the remaining comments from Reviewer 1, as per their original review.
The revised version has suffecient basic reporting now. No further comments on this section.
Experimental design has been improved, suggested experiments are added or further improved.
The authors have improved the paper after performing further research.
Although all comments are addressed,
Comment 2 seems to be pending.
Comment 8-9 needs some more explanation.
no comment
no comment
no comment
As all my comments were more or less properly addressed by the authors in the revised version of the paper, I am pleased to accept the paper for a publication.
I urge you to please carry out the revisions as recommended by the reviewers & resubmit the manuscript. Reviewer 1 has submitted a separate document with his/her comments and suggestions. In my opinion, these will result in a significantly enhanced manuscript in terms of narration, presentation, and overall contributions.
**PeerJ Staff Note:** Please ensure that all review and editorial comments are addressed in a response letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate.
**Language Note:** The review process has identified that the English language must be improved. PeerJ can provide language editing services - please contact us at copyediting@peerj.com for pricing (be sure to provide your manuscript number and title). Alternatively, you should make your own arrangements to improve the language quality and provide details in your response letter. – PeerJ Staff
The paper is well written and structured but needs changes, please see comments file.
Please see the comments. This section needs changes I have mentioned in the comments file.
Please see the comments file.
My recommendations to accept the paper after addressing the above comments.
no comment
The Following points should be included by author for the revision.
• While the study mentions that the existing MCSE system was tested only for White Gaussian noise, the types of non-stationary environmental noises tested in this study aren't specified in detail.
• There's a lack of deeper explanation on the technical workings of the DWT-CNN-MCSE system, such as the CNN architecture and specifics of the DWT preprocessing, which could benefit readers looking for technical insights.
• The research doesn't seem to factor in real-world challenges like microphone placement, distance from the sound source, or overlapping speech.
• Environmental noises pose significant challenges to speech enhancement systems, and their variability necessitates systems that can adapt to both stationary and non-stationary noises.
• The DWT-CNN-MCSE system's use of wavelet transforms and neural networks presents a promising approach to tackle the challenges of low SNRs, showing marked improvement over the BAV-MCSE approach.
• The varied performance across different SNR levels underscores the importance of designing speech enhancement systems that can dynamically adapt to different noise levels.
no comment
Suggestions:
• A deeper dive into the DWT and CNN components of the proposed system would provide readers with a better understanding of its mechanics and potential advantages.
• Simulating real-world conditions, like fluctuating distances between speakers and microphones, or handling overlapping speech, can provide insights into the system's practical applicability.
• Exploring the performance of the proposed system beyond the -10dB to 20dB range could demonstrate its resilience in more extreme noisy situations.
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