Before revision: End-to-end automatic speech recognition (ASR) systems are increasingly being favoured due to their direct treatment of the problem of speech to text conversion. However, these systems are known to be data hungry and hence underperform in low-resource settings. In this work , we propose a seemingly simple but effective technique to improve low-resource end-to-end ASR performance.
After revision: This work presents a seemingly simple but effective technique to improve low-resource end-to-end ASR performance.