Simplified Self-Attention for Transformer-based End-to-End Speech Recognition

21 May 2020Haoneng LuoShiliang ZhangMing LeiLei Xie

Transformer models have been introduced into end-to-end speech recognition with state-of-the-art performance on various tasks owing to their superiority in modeling long-term dependencies. However, such improvements are usually obtained through the use of very large neural networks... (read more)

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