Improved Meta Learning for Low Resource Speech Recognition

  title={Improved Meta Learning for Low Resource Speech Recognition},
  author={Satwinder Singh and Ruili Wang and Feng Hou},
  journal={ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  • Satwinder Singh, Ruili Wang, Feng Hou
  • Published 11 May 2022
  • Computer Science
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
We propose a new meta learning based framework for low resource speech recognition that improves the previous model agnostic meta learning (MAML) approach. The MAML is a simple yet powerful meta learning approach. However, the MAML presents some core deficiencies such as training instabilities and slower convergence speed. To address these issues, we adopt multi-step loss (MSL). The MSL aims to calculate losses at every step of the inner loop of MAML and then combines them with a weighted… 

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