PONE-D-24-28326Deep learning-based classification of speech disorder in stroke and hearing impairment: An analysis of neural network performance and clinical implicationsPLOS ONE

Dear Dr. Kim,

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Diego A. Forero, MD; PhD

Academic Editor

PLOS ONE

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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: Yes

Reviewer #2: Yes

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

Reviewer #1: Yes

Reviewer #2: Yes

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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: Yes

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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: Yes

Reviewer #2: Yes

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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 is a well-written manuscript about using deep learning to classify speech disorders in individuals with stroke and hearing impairment. I have some suggestions to improve this manuscript.

Materials and Methods

Please add details about the ground truth for this study.

Results

I believe this study would be more compelling if the authors included the confusion matrix results for each model.

Discussion

Please include a discussion on why each model achieved different accuracy levels in classifying this type of data.

Additionally, expand on the clinical applications of this system in practice.

Reviewer #2: Introduction

The authors highlight the need for this work by presenting the advantages of developing classification-based artificial intelligence models to support the diagnosis of speech disorders. The theoretical foundation of existing studies is outlined, along with the present gaps in the research.

The objective of the study is clearly stated and aligns with the title of the work.

Materials and Methods

It is recommended to specify the type of study conducted to clarify for the reader that it is retrospective.

The specifications of the equipment used are provided, as well as the Python libraries and statistical analysis tools employed.

In addition, the characteristics of the audio recordings are detailed, along with the approval by the Seoul Hospital board regarding the use of these primary source recordings.

The characteristics of the population and sample size are presented.

The procedure for recording the audio samples is described, including the details of the scripts used and the physical conditions during the recordings. A flow diagram is included to enhance the reader's comprehension.

Furthermore, the inclusion and exclusion criteria for the recordings, as well as the total number of recordings used, are outlined. The 8:1:1 ratio used for model development, testing, and validation in the machine learning system is also presented.

The methodological rigor in the development of the AI model, as well as the data selection and classification processes, is evident.

Results

The statistical results of the models are presented, demonstrating very good performance under the evaluated conditions. One model outperformed the other two presented.

Relevant statistical techniques are used to compare the models and analyze data classification.

Discussion

The discussion emphasizes important aspects such as the use of a larger dataset compared to previous studies. Accurate classification of speech disorders associated with stroke and hearing impairment is achieved, rather than merely distinguishing between normal and abnormal speakers. The analysis is based on complete scripts, allowing for a more comprehensive examination of speech patterns and characteristics, contrasting with previous studies that focused on phonation of the vowel /a/.

The discussion also highlights the advantages of analyzing features like pitch breaks, vocal fatigue, and voice breaks, which are expected to enhance the accuracy and flexibility of diagnoses.

The study's limitations primarily concern its focus on voice data in Korean and its restriction to stroke and hearing impairment, without considering other speech disorders.

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Reviewer #1: No

Reviewer #2: No

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Deep learning-based classification of speech disorder in stroke and hearing impairment

PONE-D-24-28326R1

Dear Dr. Kim,

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,

Diego A. Forero, MD; PhD

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

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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

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

Reviewer #1: 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

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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

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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: (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

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