• Dr.S.Saravanan
• P.Divya Sai
• P.Rekha
• Sk.Nawaz
• P.Sarath Chandra Reddy

In this project, we intend to investigate the ability to preserve audio classification datasets used in deep learning by fitting models to the dynamic range of the time-frequency signal of a segment. of the dataset. Previous research on audio watermarking technology required the actual sound of the watermarked audio to extract the information embedded in it. Whether the information classification model is trained using a set of watermarked information or simply using the classification results.

DIGITAL WATERMARKING FOR AUDIO CLASSIFICATION DATASETS USING LSB BASED FEATURE CLASSIFICATION FOREST APPROACH

"DIGITAL WATERMARKING FOR AUDIO CLASSIFICATION DATASETS USING LSB BASED FEATURE CLASSIFICATION FOREST APPROACH", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.c200-c205, May-2024, Available :http://www.jetir.org/papers/JETIR2405223.pdf

"DIGITAL WATERMARKING FOR AUDIO CLASSIFICATION DATASETS USING LSB BASED FEATURE CLASSIFICATION FOREST APPROACH", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppc200-c205, May-2024, Available at : http://www.jetir.org/papers/JETIR2405223.pdf