Bioacoustic-driven HCI uses sound-based signals emanating from the human body, such as voice, breathing, and physiological noises, not only to enable intuitive and adaptive systems but also to create a noninvasive and natural modality for communicating. This new paradigm nicely complements the state-of-the-art input based on touch and vision. Allowing the integration of knowledge in sensing technologies, signal analysis, and artificial intelligence, bioacoustics enables the development of systems that can dynamically respond to the physical and emotional states of their users. This chapter delivers an in-depth investigation into bioacoustic-driven HCI, starting with a general overview of bioacoustics and its adoption within interaction design. We discuss the potentialities that stem from acoustic sensors, wearable devices, and ambient microphones to record human sound patterns. The discussion goes back in time to cover processing approaches that include feature extraction, noise mitigation, and machine learning models capable of interpreting bioacoustic signals. It includes discussions on applications involving voice-controlled systems, health monitoring through acoustic biomarkers, and emotional recognition. The chapter also points out some of the challenges: real-time responsiveness, data privacy management, and ethical concerns related to user-sensitive data. Emerging trends, such as the integration of multimodal inputs and personalization, are underlined to show future perspectives in the field. By providing an overview of technologies, methodologies, and applications, this chapter offers inspiration for innovative ideas and practical adoptions in the field of bioacoustic-driven systems toward new and more intuitive paradigms of human-centered interactions.