The Role of Natural Language Processing in Abstract Dataset to Improve Virtual Assistant Devices
Reem Alshahoomi, Salma Alameri, Sanaa Alfalasi, Feras N. Al-Obeidat · Procedia Computer Science · 2025
Abstract—Natural Language Processing (NLP) has transformed human-computer interaction, especially in the realm of virtual assistants. NLP enables machines to understand, interpret, and generate human language, driving innovations in applications ranging from virtual assistants to customer service chatbots. This paper delves into the intersection of NLP and virtual assistants, examining advanced models like BERT and RoBERTa, which enhance contextual understanding and user intent recognition. Through a comprehensive evaluation using the dataset of research abstracts to explore new methods and improve response for virtual assistant devices, it explores methods to improve model efficiency, precision, and scalability. By leveraging machine learning techniques and probabilistic models such as Naive Bayes and Hidden Markov Models, this research addresses key challenges in language comprehension and response accuracy. It also discusses the potential for smaller, more efficient models to optimize virtual assistant performance in real-time applications. The results highlight the ongoing advancements in NLP, aiming for a future where virtual assistants become more responsive, intuitive, and capable of supporting various industries with increased efficiency.