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Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2993924
Abstract: In recent decades, many researchers pay a lot of attention on generating informative responses in end-to-end neural dialogue systems. In order to output the responses with knowledge and fact, many works leverage external knowledge to…
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Keywords:
reinforcement learning;
response generation;
model;
knowledge driven ... See more keywords
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Published in 2022 at "Computational Intelligence"
DOI: 10.1111/coin.12544
Abstract: Task‐oriented dialogue system (TOD) is one kind of application of artificial intelligence (AI). The response generation module is a key component of TOD for replying to user's questions and concerns in sequential natural words. In…
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Keywords:
oriented dialogue;
task oriented;
response generation;
mechanism ... See more keywords
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Published in 2023 at "PLOS ONE"
DOI: 10.1371/journal.pone.0280458
Abstract: Neural open-domain dialogue systems often fail to engage humans in long-term interactions on popular topics such as sports, politics, fashion, and entertainment. However, to have more socially engaging conversations, we need to formulate strategies that…
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Keywords:
grounded conversation;
adversarial network;
emotion;
generative adversarial ... See more keywords
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Published in 2023 at "Applied Sciences"
DOI: 10.3390/app13085109
Abstract: It is important for chatbots to emotionally communicate with users. However, most emotional response generation models generate responses simply based on a specified emotion, neglecting the impacts of speaker’s personality on emotional expression. In this…
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Keywords:
personality;
response generation;
emotional response;
model ... See more keywords