Verbal Description to Facial Sketch Converter

“Verbal Description to Facial Sketch Converter”

Asst. Prof. T.S. Palorkar*1, Aditi Dewalkar*2, Vrushali Rahangdale*3, Aman Shahare*4, Saniya Sheikh*5
*1Project Guide, Department Of Computer Science & Engineering, Priyadarshini J.L College Of Engineering, Nagpur, Maharashtra, India.

*2,3,4,5,6Department Of Computer Science & Engineering, Priyadarshini J.L College Of Engineering, Nagpur, Maharashtra, India.

ABSTRACT
Recent advancements in artificial intelligence have significantly transformed forensic science, particularly in the domain of criminal identification. This study presents a novel AI-driven system that generates facial sketches based on verbal descriptions provided by eyewitnesses. Leveraging natural language processing (NLP), computer vision, and deep learning—particularly generative adversarial networks (GANs)—the system translates spoken input into visual representations of suspects. Designed to support law enforcement agencies, the tool aims to streamline and automate the process of composite sketch creation from eyewitness accounts. The research encompasses a comprehensive literature review, architectural design, and prototype implementation to assess the system's feasibility and performance. Preliminary results demonstrate encouraging accuracy in producing facial images that reasonably resemble the described individuals, underscoring the promise of speech-to-sketch technology in digital forensic investigations.

Keywords: Forensic AI, Speech-to-Sketch Generation, Natural Language Processing (NLP), Generative Adversarial Networks (GANs), Facial Reconstruction, Multimodal Artificial Intelligence, Witness Testimony Interpretation, Text-to-Image Synthesis, Law Enforcement Technology, Automated Criminal Identification.