Emotion recognition from textual input using an emotional semantic network

نویسندگان

  • Ze-Jing Chuang
  • Chung-Hsien Wu
چکیده

This paper presents an emotion recognition system with textual input. In this system, an emotional semantic network is proposed to extract the semantic information related to emotion. The semantic network is composed of two subnetworks: a static semantic network and a dynamic semantic network. The static semantic network is established from an existing Chinese knowledge base called HowNet and used to estimate the emotion trigger value of each word. The dynamic semantic network accepts the textual input and dynamically constructs the nodes and links, which represent the emotion carrier and the emotion propagator respectively. Initiated by the emotion trigger value, the emotion in the dynamic semantic network will propagate and finally converge to the final emotion output. Experimental results show an encouraging achievement was obtained.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Bimodal Emotion Recognition from Speech and Text

This paper presents an approach to emotion recognition from speech signals and textual content. In the analysis of speech signals, thirty-seven acoustic features are extracted from the speech input. Two different classifiers Support Vector Machines (SVMs) and BP neural network are adopted to classify the emotional states. In text analysis, we use the two-step classification method to recognize ...

متن کامل

Java Tutoring System with Facial and Text Emotion Recognition

This paper presents the design and implementation of an intelligent tutoring system (ITS) for teaching JAVA, which can recognize the user's emotional state through facial expressions and textual dialogues. For facial emotion recognition we implemented a neural network with WEKA library and a facial feature extractor with OPENCV library. The ITS applies a semantic algorithm (ASEM) to extract tex...

متن کامل

Multi-Modal Emotion Recognition from Speech and Text

This paper presents an approach to emotion recognition from speech signals and textual content. In the analysis of speech signals, thirty-three acoustic features are extracted from the speech input. After Principle Component Analysis (PCA) is performed, 14 principle components are selected for discriminative representation. In this representation, each principle component is the combination of ...

متن کامل

MEMN: Multimodal Emotional Memory Network for Emotion Recognition in Dyadic Conversational Videos

Multimodal emotion recognition is a developing field of research which aims at detecting emotions in videos. For conversational videos, current methods mostly ignore the role of inter-speaker dependency relations while classifying emotions. In this paper, we address recognizing utterance-level emotions in dyadic conversations. We propose a deep neural framework, termed Multimodal Emotional Memo...

متن کامل

Emotion recognition from speech using prosodic features

Emotion recognition, a key step of affective computing, is the process of decoding an embedded emotional message from human communication signals, e.g. visual, audio, and/or other physiological cues. It is well-known that speech is the main channel for human communication and thus vital in the signalling of emotion and semantic cues for the correct interpretation of contexts. In the verbal chan...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2002