From decoding-driven to detection-based paradigms for automatic speech recognition

We present a detection-based automatic speech recognition (ASR) paradigm that is capable of integrating both the knowledge sources accumulated in the speech science community and the modeling techniques established in the speech processing community. By exploring this new framework, we expect that researchers in the Interspeech community can collaboratively contribute to developing next generation algorithms that have the potential to surpass current capabilities, and go beyond the limitations of the state-of-the-art ASR technologies.