Transformer-based Acoustic Modeling for Hybrid Speech Recognition
ICASSP, pp. 6874-6878, 2019.
We propose and evaluate transformer-based acoustic models (AMs) for hybrid speech recognition. Several modeling choices are discussed in this work, including various positional embedding methods and an iterated loss to enable training deep transformers. We also present a preliminary study of using limited right context in transformer mo...More
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