Papers with CopyNet
Converting the Point of View of Messages Spoken to Virtual Assistants (2020.findings-emnlp)
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| Challenge: | Using a voice message, virtual assistants extract the message and send it to the user’s contact, rather than properly converting it to “I love you.” |
| Approach: | They propose to take a voice message from one user, convert it to “I love you” and deliver it to its target user. |
| Outcome: | The proposed system can take a voice message from one user, convert the point of view of the message, and then deliver the result to its target user. |
Unsupervised Context Rewriting for Open Domain Conversation (D19-1)
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| Challenge: | Existing approaches to model conversation context have drawbacks, such as lack of coreferences and long dependency. |
| Approach: | They propose a context rewriting method which explicitly rewrites the last utterance by considering context history. |
| Outcome: | The proposed method outperforms baselines in terms of rewriting quality, multi-turn response generation, and end-to-end retrieval-based chatbots. |
Learning to Copy for Automatic Post-Editing (D19-1)
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| Challenge: | Automatic post-editing (APE) is an important task in natural language processing. |
| Approach: | They propose a method that explicitly models how to copy words from a machine translation to a correct translation. |
| Outcome: | The proposed method outperforms all published methods on the WMT 2016-2017 datasets. |