PONE-D-24-37227Target sample mining with modified activation residual network for speaker verificationPLOS ONE

Dear Dr. Chaoqun,

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Qian Zhang, Ph.D

Academic Editor

PLOS ONE

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Additional Editor Comments:

We note that one or more reviewers has recommended that you cite specific previously published works. As always, we recommend that you please review and evaluate the requested works to determine whether they are relevant and should be cited. It is not a requirement to cite these works. We appreciate your attention to this request.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: I Don't Know

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: No

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: No

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This paper introduces a novel neural network architecture termed ResNet-P, which is constructed on the foundation of the Residual Network (ResNet) and incorporates a Parametric Rectified Linear Unit (PReLU) activation function. This modification is designed to enhance the network's capability to represent features and to mitigate issues related to gradient flow. Furthermore, the paper proposes an adaptive target function named SphereSpeaker, which is specifically tailored to optimize sample mining in speaker verification tasks. By incorporating strategies for balancing positive and negative samples and for mining challenging samples, the paper further refines the model's ability to handle imbalanced data during training, thereby improving the model's convergence rate and generalization capabilities. To diminish the overlap in similarity scores between positive and negative sample pairs, the paper introduces a method for adjusting similarities. Experiments conducted on the VoxCeleb1 database substantiate the efficacy of the proposed methods. However, the authors must address the following issues:

1. The paper exhibits subpar writing quality, with several sentences not adhering to standard academic expression. For instance, the phrase "This new network is named the Residual Network-PReLu, ResNet-P." should be rephrased for clarity and formality. Additionally, the use of "This chapter proposes..." in the Conclusion section is somewhat perplexing. The arbitrary naming of numerous acronyms also detracts from the manuscript's scholarly tone. It is recommended that the author revise the entire text for clarity, consistency, and adherence to academic writing standards.

2. The current manuscript appears to be a mere assemblage of technical elements without a coherent logical progression, which may impede the readers' comprehension. The author is advised to restructure the organization of the paper to enhance clarity and facilitate understanding.

3. The author's comparison of algorithms is outdated and does not reflect the current state of the art in speaker verification. It is recommended that the author updates the comparative analysis to include the most advanced algorithms in the field, such as transformer-based methods, to ensure the manuscript's relevance and contribution to the academic discourse.

4. The author claims to have proposed a novel neural network architecture, namely ResNet-P (Residual Network-PReLu). However, it appears that numerous publications have already employed the combination of ResNet and PReLU, as referenced in [1-3]. Consequently, the innovative aspect of this manuscript seems insufficient. It is suggested that the author either provides a more substantial contribution or clearly delineates how their work differs from and improves upon the existing literature.

[1] Peng, S., Huang, H., Chen, W., Zhang, L., & Fang, W. (2020). More trainable inception-ResNet for face recognition. Neurocomputing, 411, 9-19.

[2] Trottier, L., Giguere, P., & Chaib-Draa, B. (2017, December). Parametric exponential linear unit for deep convolutional neural networks. In 2017 16th IEEE international conference on machine learning and applications (ICMLA) (pp. 207-214). IEEE.

[3] Zhao, M., Zhong, S., Fu, X., Tang, B., Dong, S., & Pecht, M. (2020). Deep residual networks with adaptively parametric rectifier linear units for fault diagnosis. IEEE transactions on industrial electronics, 68(3), 2587-2597.

5. The placement of the result figures at the end of the manuscript is not reader-friendly, as it disrupts the flow of information. Additionally, in Figure 3, the subfigures (e) and (f) are not aligned, which affects the visual presentation. It is recommended that the author reorganizes the manuscript to present the results in a more logical sequence as they are discussed in the text and ensures that all visual elements, such as figures, are properly aligned and formatted for clarity and aesthetic consistency.

Reviewer #2: The study proposes a methodology to overcome some limitations in using traditional SoftMax methods. The writer proposed three methods and concluded that they enhance the accuracy of speaker verification tasks.

I think the study is trying to propose solutions to some limitations that can be very useful in the field. However, I think the writer should write more clearly to elevate the level of the paper and make it easier to follow. So, my recommendation is that the writers should edit the writing and add a discussion section then re-submit, if possible.

Here are some comments per section

The Abstract

It took the writer long to set the aim for the study. The abstract has to be concise and talks a bit about the background, the aim of the study, the methods used and the results of the study.

- The writers suggested a method to overcome some limitation with using SoftMax, but didn’t mention anything about the findings at the end of the abstract.

- Please avoid using ‘ novel’ when you propose a method/ an idea.

- I would avoid using ‘has drawbacks’ in the abstract, and instead use ‘some limitations’.

- When you talk about training, mention it is in machine learning. The abstract has to be understood without going back to other parts of the manuscript.

- The second sentence needs paraphrasing, it reads as if the discrepancy between predicted probability and the actual distribution is caused by the fact that SoftMax framework is suitable for multi-class classification problem in verification and training. Is that only SoftMax or are there joint functions that are used to make sure that there are no such discrepancies such as using loss function. Either way, please paraphrase for clarity.

- SoftMax instead of softmax

- As in the abstract we need to mention the methods used, it would be beneficial if you could explain in line or two what is the suggested method and what does it do?// what does it add to the ‘traditional methods’.

- You need to include the findings at the end of the abstract.

- The abstract and the conclusion should align, is it only one suggested method or three suggested methods?

Introduction

- The first part of the introduction reads as if the writer is listing the methods, some connection would help coherence.

- Please connect between paragraphs.

- Each paragraph should have a topic sentence that relates to the previous point, then all the sentences in the paragraph should explain link to other studies and you should critically say how is this point support your study follow PEEL & PEELC methods in writing paragraphs, please.

- In stead of saying ‘this section will…’ try to have some connection even with the use of subheadings.

- Add a Space between ‘.’ And the new sentences, please.

- Use references please when you talk about problems and the issues you raised.

- Avoid starting sentences with ‘and’ please.

- When introducing the data, just start talking about the data straight forward, please.

- You should have a subsection after talking about the data, which might be called ‘procedure’ what you did with the data. This helps the readers follow smoothly.

Experimental analysis

The first sentence here has to align with the objective of the study that you mentioned in the abstract and the conclusion. This has to be clarified in writing. Your proposed model is to use deep residual network and adaptive functions to improve speaker verification systems?, so make sure to emphasize that point.

This chapter would benefit from a discussion section where you present your results, explain them in relation to previous work in the field.

Conclusion

o This section starts by saying that there is a speaker verification method, but later on in the paragraph you say “The experimental results indicate that all three proposed methods can enhance the accuracy of speaker verification tasks”. You need to be precise and clear from the first sentence.

o Please paraphrase this sentence “the stability and accuracy of deep networks in expressing speaker characteristics, and from the perspective of performance analysis in various aspects, the methods exhibit good performance”

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Reviewer #1: No

Reviewer #2: No

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Attachments

Attachment

Submitted filename: Comments for Author and Editors-D-24-37227.docx

Target sample mining with modified activation residual network for speaker verification

PONE-D-24-37227R1

Dear Dr. Chaoqun,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Qian Zhang, Ph.D

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors have done a good job of addressing the issues I raised and all comments have been addressed and recommended for publication in this journal.

Reviewer #2: (No Response)

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

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