AI-Powered Voice Assistants: A Review Of Speech Recognition, Language Understanding, Speech Synthesis And Security

An AI-powered voice assistant lets people interact with computers and devices through natural speech rather than keyboard and mouse. It recognizes spoken commands, understands the user's intent, performs an action and replies with synthesized speech. This paper reviews the end-to-end speech pipeline that makes voice assistants possible. It covers wake-word detection with small-footprint neural networks, automatic speech recognition from early deep acoustic models to recurrent, transformer-based and self-supervised systems trained on large and diverse audio, spoken language understanding through intent classification and slot filling, dialogue and action execution, and neural text-to-speech that produces natural voices. Evaluation measures such as word error rate and intent accuracy are explained, and the security of voice interfaces against hidden and inaudible commands is examined. A five-layer architecture comprising audio capture, speech recognition, language understanding, action execution and speech output is proposed, along with a research gap analysis, objectives and a comparison of speech recognition approaches. Accessibility benefits for students, professionals and people with disabilities are discussed. The review concludes that modern speech and language models enable simple, hands-free and efficient human–computer interaction, provided that accuracy for diverse accents, privacy and voice security are addressed.