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• Improved training of end-to-end attention models for speech recognition
  2018 · 281 citations
• Language Modeling with Deep Transformers
  2019 · 177 citations
• RETURNN as a Generic Flexible Neural Toolkit with Application to Translation and Speech Recognition
  2018 · 77 citations
• On Using SpecAugment for End-to-End Speech Translation
  2019 · 23 citations
• On using 2D sequence-to-sequence models for speech recognition
  2019 · 9 citations
• A study of latent monotonic attention variants
  2021 · 7 citations
• A systematic comparison of grapheme-based vs. phoneme-based label units for encoder-decoder-attention models
  2020 · 5 citations
• Equivalence of Segmental and Neural Transducer Modeling: A Proof of Concept
  2021 · 4 citations
• Gradient-Based Speech-to-Text Alignment for Any ASR Model: From CTC to Speech LLMs