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Federated Learning for Speech Recognition: Revisiting Current Trends Towards Large-Scale ASR

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This paper, accepted for the NeurIPS 2023 workshop, discusses the overlooked potential of automatic speech recognition (ASR) in federated learning (FL) and differential privacy (DP), highlighting ASR’s suitability as a benchmark due to its data distribution and real-world relevance.

Federated Learning for Speech Recognition: Revisiting Current Trends Towards Large-Scale ASR

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Federated Learning: The Future of Speech Recognition

This paper was accepted at the Federated Learning in the Age of Foundation Models workshop at NeurIPS 2023.
While automatic speech recognition (ASR) has seen impressive advancements, it often doesn’t get the attention it deserves within the federated learning (FL) and differential privacy (DP) communities. However, ASR is an excellent test for FL and DP because:

  • Natural data split: User data is divided by speaker information.
  • Heterogeneous data: Data varies across speakers, mimicking real-world scenarios.
  • Acoustic and language modeling: ASR involves both, offering a complex challenge.

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