DARTS-ASR: Differentiable Architecture Search for Multilingual Speech Recognition and Adaptation

Understand

In previous works, only parameter weights of ASR models are optimized under fixed-topology architecture.

• However, the design of successful model architecture has always relied on human experience and intuition.
• Besides, many hyperparameters related to model architecture need to be manually tuned.
• Therefore in this paper, we propose an ASR approach with efficient gradient-based architecture search, DARTS-ASR.