Advancing CTC-CRF Based End-to-End Speech Recognition with Wordpieces and Conformers

Understand

Automatic speech recognition systems have been largely improved in the past few decades and current systems are mainly hybrid-based and end-to-end-based.

• The recently proposed CTC-CRF framework inherits the data-efficiency of the hybrid approach and the simplicity of the end-to-end approach.
• In this paper, we further advance CTC-CRF based ASR technique with explorations on modeling units and neural architectures.
• Specifically, we investigate techniques to enable the recently developed wordpiece modeling units and Conformer neural networks to be succesfully applied in CTC-CRFs.