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eess.AS2020
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…
eess.AS2020
Full-Sum Decoding for Hybrid HMM based Speech Recognition using LSTM Language Model
Wei Zhou, Ralf Schlüter, Hermann Ney
In hybrid HMM based speech recognition, LSTM language models have been widely applied and achieved large improvements. The theoretical capability of modeling any unlimited context…
eess.AS2020
The RWTH ASR System for TED-LIUM Release 2: Improving Hybrid HMM with SpecAugment
Wei Zhou, Wilfried Michel, Kazuki Irie +3
We present a complete training pipeline to build a state-of-the-art hybrid HMM-based ASR system on the 2nd release of the TED-LIUM corpus. Data augmentation using SpecAugment is su…