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Combining semantic search and twin product classification for recognition of purchasable items in voice shopping
To overcome this problem, we present a framework that (1) uses a retrieval module that returns the most rele- vant products with respect to the detected slot, and (2) combines it with a twin network that decides if the detected slot is indeed a pur- chasable item or not.
It is better to Verify: Semi-Supervised Learning with a human in the loop for large-scale NLU models
When a NLU model is updated, new utter- ances must be annotated to be included for training.
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