Based on sentence similarity and emotion conversation for spoken dialogue system
Bo-Hao Su, Shih-Pang Tseng, Jhing-Fa Wang, Jhong-Cian Huang · 2017
This paper presents the based-on question answering system for spoken dialogue. Utilizing sentence similarity to calculate the score and finding the corresponding sentence are main parts. When the corpus is insufficient, the user-generated answer is generated form Free Talk. In our system, the ASR transcription is processed through Chinese Knowledge and Information Processing (CKIP) Chinese words segmentation system. Then, filtering the command sentences through human machine interface, remaining normal sentences are passed the dialogue system, and normal sentences are vectorized through preprocess bag of word. All sentences of corpus have been preprocessed and vectorized in vector space model, then, input sentence is calculated by sentence similarity with vector space model. In order to make system more enjoyable, we adapt image recognition to record the round emotions. According to the round emotions, to response the emotion conversation.