Papers with gated neural network

1 papers
Gated Embeddings in End-to-End Speech Recognition for Conversational-Context Fusion (P19-1)

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Challenge: Existing speech recognition systems are built at individual, isolated utterance level to make building systems computationally feasible.
Approach: They propose to use text-based external word and/or sentence embeddings to integrate conversational context information into a single neural network model.
Outcome: The proposed model outperforms standard end-to-end speech recognition models on the Switchboard conversational speech corpus and improves word error rate with better conversational-context representation.

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