173 citations · 306 across the 58 of their papers we have counts for
5 papers · 1 filter
Analyzing the Importance of Blank for CTC-Based Knowledge Distillation
Benedikt Hilmes, Nick Rossenbach, Ralf Schlüter
With the rise of large pre-trained foundation models for automatic speech recognition new challenges appear. While the performance of these models is good, runtime and cost of infe…
Classification Error Bound for Low Bayes Error Conditions in Machine Learning
Zijian Yang, Vahe Eminyan, Ralf Schlüter +1
In statistical classification and machine learning, classification error is an important performance measure, which is minimized by the Bayes decision rule. In practice, the unknow…
End-to-End Training of a Neural HMM with Label and Transition Probabilities
Daniel Mann, Tina Raissi, Wilfried Michel +2
We investigate a novel modeling approach for end-to-end neural network training using hidden Markov models (HMM) where the transition probabilities between hidden states are modele…
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…
RETURNN: The RWTH Extensible Training framework for Universal Recurrent Neural Networks
Patrick Doetsch, Albert Zeyer, Paul Voigtlaender +3
In this work we release our extensible and easily configurable neural network training software. It provides a rich set of functional layers with a particular focus on efficient tr…