A transformer speech encoder can learn to internally rearrange audio information into text order, enabling a lightweight decoder trained with simple cross-entropy to nearly match RNN-Transducer accuracy with faster inference.
Attention-based models for speech recognition
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Aligner-Encoders: Self-Attention Transformers Can Be Self-Transducers
A transformer speech encoder can learn to internally rearrange audio information into text order, enabling a lightweight decoder trained with simple cross-entropy to nearly match RNN-Transducer accuracy with faster inference.