Neelam Gupta Reviewer
02 Dec 2025 11:01 AM
Approved
1. Relevance and Originality
The paper examines a highly relevant subject by addressing the preservation of historical sound environments through advanced digital techniques. The intersection of cultural heritage, architectural acoustics, and contemporary artificial intelligence provides a unique angle that adds strong originality to the research. The focus on reconstructing long lost auditory experiences positions the work as an innovative contribution within heritage science.
2. Methodology
The study references several technical approaches such as three dimensional modelling, acoustic simulation, and AI supported analysis. While these approaches appear appropriate, the methodological discussion would benefit from clearer details about the modelling parameters, the types of algorithms used, and the procedures applied to validate the simulated acoustic results. Providing more structured descriptions would offer greater transparency into the research design.
3. Validity and Reliability
The use of historical architectural information alongside machine learning to predict acoustic behaviour is promising. However, the reliability of the outcomes depends on how accurately the historical materials, spatial geometries, and environmental attributes were captured. The paper would be strengthened by describing any reference measurements, comparative tests, or uncertainty assessments that support the predictive accuracy of the models.
4. Clarity and Structure
The writing presents a clear narrative that explains why historic soundscapes matter and how technology can help preserve them. The structure is generally smooth, though some segments combine conceptual and technical elements too closely. Separating the cultural context from the computational workflow would make the argument even clearer and easier for the reader to navigate.
5. Results and Analysis
The discussion highlights the potential of AI guided acoustic reconstruction, especially for restoration and educational scenarios. To enhance the analytical depth, the paper could include representative findings such as predicted reverberation characteristics, resonance patterns, or examples from the case studies. Even a brief illustration of the model outputs would reinforce the practical value of the research.
Neelam Gupta Reviewer