Automatic Speech Recognition System

Automatic Speech Recognition (ASR) systems aim to accurately convert spoken language into text, a crucial task with broad applications. Current research heavily focuses on improving accuracy and robustness through techniques like end-to-end models (e.g., conformer transducers), large language model integration for error correction and rescoring, and addressing biases in ASR performance across different dialects and languages. These advancements are vital for enhancing the accessibility and usability of speech-based technologies in various fields, from healthcare and assistive technologies to virtual assistants and language documentation.