Concept of Speaker Age Estimation Using Neural Networks to Reduce Child Grooming

Abstract

This paper focusses on using neural network models to predict the age of social media users based on their voice recordings. The objective is to identify potential risky interactions between minors and adults by comparing the declared and predicted age groups of the users. The paper addresses the selection and training of suitable models and evaluates their effectiveness in age prediction. The results are demonstrated in sample data, where performance metrics are analysed, and possible limitations of the method are identified. Finally, the implications of the results for the safety of minors on social networks are discussed, and suggestions for future research in this area are provided.

Keywords

• convolutional neural networks
• deep learning
• grooming detection
• human voice
• social networking (online)