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Method and System of Implanting Emotion into Text Disclosure Number: IPCOM000248929D
Publication Date: 2017-Jan-22
Document File: 4 page(s) / 583K

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The Prior Art Database


Traditional work only focuses on sentiment/emotion analysis of text. The invented system implants emotion (anger, happiness, sadness, fear, surprise, disgust, etc.) with different intensity into text sentence. It provides affective response for conversation/dialog system. It uses template-based and ontology-based methods to implant the most suitable emotion into text.

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Method and System of Implanting Emotion into Text

1. The problem

Almost all conversation/dialog systems cannot generate affective sentences. However, in order to build an empathic system and make the user

feel more comfortable, implanting emotions into text is indispensable. For example, happy feeling can be implanted into the original response “I

receive your letter”, and the affective response “I am so glad to receive your letter!” can be generated.

2. Main Idea

Based on domain specific emotion ontology and emotion dictionary, two major methods are adopted in the invented system to implant emotion

into text: template-based method and corpus-based method.

3. How it works

(1) System Framework

As shown in Figure 1, in the invention, there are three components: sentence analyzer, emotion analysis, and emotion implantation. Emotion

implantation consists of two kinds of modules: corpus-based emotion implantation and templated-based emotion implantation.


Figure 1: System framework

(2) Corpus-based Method

Corpus-based emotion implantation method is used to imitate natural emotion response. As shown in Figure 2, after a target sentence with

similar structure and target emotion is found, the words that convey emotion are transferred to the original response.

Figure 2: Corpus-based emotion implantation method

(3) Template-based method

Template-based emotion implantation method is used to insert emotion words directly into original sentences. There are two ways to achieve this