This work investigates the effectiveness of incorporating paralinguistic feature extraction in audio deepfake detection models. The proposed model extracts paralinguistic features from audio clips and represents them as 1024-dimensional vector embeddings. These embeddings are then used as input for a logistic regression model, which performs binary classification to distinguish between real and deepfake audio samples. The ASVspoof2019 dataset, comprising both genuine and spoofed audio clips, is used to evaluate the model's performance. The results are assessed using evaluation metrics such as Equal Error Rate (EER) and accuracy, which provide insight into the model's effectiveness compared t... More >

Artificial intelligence (AI) is transforming the financial sector by revolutionizing risk management and enhancing personalized banking experiences. This study examines the role of AI in finance by analyzing how companies such as AlphaSense and Kasisto utilize AI-driven solutions to optimize financial decision-making and customer interactions. AI’s advanced capabilities in data analysis, credit underwriting, and automated customer service have significantly enhanced efficiency, accuracy, and accessibility within the financial services sector. The paper explores key AI technologies, including machine learning, natural language processing (NLP), and generative AI, which drive this transforma... More >