A systematic comparison of grapheme-based vs. phoneme-based label units for encoder-decoder-attention models

1 code implementation • 19 May 2020 • Mohammad Zeineldeen, Albert Zeyer, Wei Zhou, Thomas Ng, Ralf Schlüter, Hermann Ney

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 based on e. g. byte-pair encoding (BPE).

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1