23 citations · 48 across the 5 of their papers we have counts for
14 papers
Monotonic segmental attention for automatic speech recognition
Albert Zeyer, Robin Schmitt, Wei Zhou +2
We introduce a novel segmental-attention model for automatic speech recognition. We restrict the decoder attention to segments to avoid quadratic runtime of global attention, bette…
Why does CTC result in peaky behavior?
Albert Zeyer, Ralf Schlüter, Hermann Ney
The peaky behavior of CTC models is well known experimentally. However, an understanding about why peaky behavior occurs is missing, and whether this is a good property. We provide…
Investigating Methods to Improve Language Model Integration for Attention-based Encoder-Decoder ASR Models
Mohammad Zeineldeen, Aleksandr Glushko, Wilfried Michel +3
Attention-based encoder-decoder (AED) models learn an implicit internal language model (ILM) from the training transcriptions. The integration with an external LM trained on much m…
Librispeech Transducer Model with Internal Language Model Prior Correction
Albert Zeyer, André Merboldt, Wilfried Michel +2
We present our transducer model on Librispeech. We study variants to include an external language model (LM) with shallow fusion and subtract an estimated internal LM. This is just…
A study of latent monotonic attention variants
Albert Zeyer, Ralf Schlüter, Hermann Ney
End-to-end models reach state-of-the-art performance for speech recognition, but global soft attention is not monotonic, which might lead to convergence problems, to instability, t…
A systematic comparison of grapheme-based vs. phoneme-based label units for encoder-decoder-attention models
Mohammad Zeineldeen, Albert Zeyer, Wei Zhou +3
Following the rationale of end-to-end modeling, CTC, RNN-T or encoder-decoder-attention models for automatic speech recognition (ASR) use graphemes or grapheme-based subword units…