Abstract

Human-computer interaction (HCI) has evolved significantly with speech processing technologies, yet a substantial gap remains between natural human communication and machine interaction capabilities. This paper examines speech processing's role in enhancing HCI by analyzing acoustic signal processing, natural language understanding, and user interface design. The study investigates key technologies including automatic speech recognition (ASR), text-to-speech synthesis, and speaker identification across diverse applications such as voice assistants, accessibility tools, gaming environments, and interactive voice response systems. Our analysis reveals that while speech processing has successfully transformed HCI applications, critical issues including acoustic noise sensitivity, limited inclusivity for diverse speaker populations, and the “uncanny valley” effect continue impeding optimal user experience.