Amazon Technologies, Inc.

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Arindam Mandal

Premkumar Natarajan

Jing Huang

Anjali Yuan Narayan-Chen

Jiao Sun

Yang Liu

Tagyoung Chung

Shuyang Gao

Nanyung Peng

Alessandra Cervone

Nanyun Peng

In accordance with one disclosed method, first data representing first text may be processed using a first machine learning model configured to generate second data representing an explanation as to why the first text is humorous. The second data may be processed, together with the first data, by a second machine learning model configured to generate a value indicating that the first data and the second data correspond to a pun. A device may be caused to take at least a first action based at least in part on the value.

Virtual assistant humor management

In accordance with one disclosed method, first data representing one or more first keywords may be processed by at least one first component to determine a first pair of words suitable for generating a pun. The first pair of words may then be processed using a first machine learning model configured to generate an output pun based at least in part on one or more input keywords and an input word pair such that the output pun is contextually related to the one or more input keywords. A first pun that is contextually related to the one or more first keywords may be received from the first machine learning model, and a first device may be caused to output a representation of the first pun.

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Santa Clara, CA, United States of America

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