ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning
ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning
End-to-end automatic speech recognition (ASR) models are increasingly large and complex to achieve the best possible accuracy.In this paper, we build an AutoML system that uses reinforcement learning (RL) to optimize the per-layer compression ratios when applied to a state-of-the-art attention based end-to-end ASR model composed of several LSTM layers.We …