Embedded Signal Processing for Audio and Speech Recognition Applications

Abstract

The amalgamation of embedded signal processing within audio and speech recognition systems has catalyzed a paradigm shift in human-machine interaction. This article navigates the intricate landscape of this transformative technology, delving into the fusion of sophisticated signal processing algorithms within embedded systems. It examines how these techniques empower devices to decode, analyze, and respond to the intricacies of human speech and sound. The abstract begins by elucidating the fundamental principles behind audio recognition within embedded systems, outlining the foundational role of signal processing in decoding acoustic patterns. It progresses to explore the complexities of speech recognition, traversing beyond sound interpretation to navigate the subtleties of language and semantics. Furthermore, this article underscores the transformative impact of embedded signal processing across diverse industries and applications. It sheds light on the birth of voice-activated assistants, advancements in automated speech-to-text translation, and the augmented accessibility embedded signal processing has unlocked across various technologies. Through an in-depth exploration of challenges, advancements, and real-world implementations, this article unravels the pivotal role of embedded signal processing in shaping the evolution of audio and speech recognition technologies. It illuminates the transformative potential of this domain, offering insights into the future trajectory and possibilities in this dynamic technological landscape.