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@article{201077,
        author = {Mrs. J Veerendeshwari and Miss. Maheswari M and Miss. Jagadeeswari V and Miss. Nandhini D},
        title = {Suspect Speech AI: An Intelligent System for Detecting Suspicious Speech Patterns},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {no},
        pages = {337-343},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=201077},
        abstract = {With the rapid growth of digital communication, monitoring and identifying suspicious speech has become increasingly important for security and safety. This project, Suspect Speech AI, focuses on developing an intelligent system that can analyze spoken or textual communication and detect potentially harmful or suspicious content. The system uses Natural Language Processing (NLP) and Ma-chine Learning techniques to classify speech patterns based on predefined categories such as threat, abuse, or normal communication. The proposed solution aims to assist law enforcement agencies, social media platforms, and organizations in early detection of harmful intent. The model is trained using labeled datasets and evaluated for accuracy and efficiency. The results demonstrate that AI-based speech analysis can significantly improve monitoring systems while maintaining scalability and reliability. The system workflow includes several important stages. Initially, the input, whether it is text or converted speech, is preprocessed to remove noise, irrelevant words, and in-consistencies. Following this, feature extraction techniques such as TF-IDF and word embeddings transform the input into a format suitable for machine learning algorithms. The model is trained using labeled datasets containing examples of normal and suspicious communication patterns. After training, the system is evaluated using performance metrics like accuracy, precision, recall, and F1-score to ensure reliability and efficiency. One of the key advantages of the Suspect Speech AI system is its scalability. It can handle large volumes of data generated across social media, messaging platforms, or organizational communication channels. Moreover, it pro-vides real-time classification, which is critical for early detection and timely response to potential threats. This makes it highly useful for law enforcement agencies, social media platforms, cybersecurity systems, and organizations seeking to monitor communication effectively. To address these challenges, the Suspect Speech AI system has been developed as an automated, intelligent solution. This system leverages Artificial Intelligence (AI), Natural Language Processing (NLP), and Machine Learning (ML) techniques to analyze both textual and spoken communication and detect potentially harmful or suspicious content. By classifying speech into categories such as normal, abusive, or threatening, the system allows organizations and authorities to identify dangerous communication in real-time. In conclusion, the Suspect Speech AI project demonstrates how advanced AI techniques can improve safety and security by automating the detection of suspicious communication. The system not only reduces human effort and error but also ensures a faster, more reliable, and scalable approach to monitoring large-scale digital communication. Its integration into various platforms can significantly enhance the early detection of harmful content, prevent potential risks, and promote safer communication environments.},
        keywords = {Artificial Intelligence, Natural Language Processing, Speech Analysis, Machine Learning, Security},
        month = {May},
        }