Computers lack empathy, but researchers from China are looking to change that with their deep learning-based chatbot capable of assessing the emotional content of a conversation and responding accordingly.
The work opens the door to a new generation of chatbots that are emotionally aware. “To the best of our knowledge, this is the first work addressing the emotion factor in large-scale conversation generation,” mentions the researchers in their paper.
Using TITAN X GPUs, and cuDNN with the TensorFlow deep learning framework, the researchers trained their model on a dataset of 23,000 sentences collected from the Chinese blogging service Weibo and manually annotated with their emotional charge – anger, disgust, happiness, like, sadness. They then used an ordinary chatbot conversation generator to produce responses and utilized their deep learning algorithm called Emotional Chatting Machine (ECM) to ensure the response has the correct emotional content.
For example, to reply to the statement “Worst day ever. I arrived late because of the traffic,” the ECM generates different responses, depending on the required emotion.
For happiness, it responds, “Keep smiling! Things will get better.” For sadness, it responds, “It’s depressing.” For disgust, it says, “Sometimes life just sucks.” For anger, it says, “The traffic is too bad!” And to express liking, it says, “I am always here to support you.”
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AI-Generated Summary
- Researchers from China have developed a deep learning-based chatbot that can assess the emotional content of a conversation and respond accordingly, marking a significant step towards emotionally aware chatbots.
- The Emotional Chatting Machine (ECM) algorithm was trained on a dataset of 23,000 sentences from the Chinese blogging service Weibo, annotated with emotions such as anger, disgust, happiness, and sadness.
- The ECM generates responses based on the required emotion, demonstrating its ability to produce emotionally relevant and varied responses to user input.
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