Emotion reply automatic generation method for open domain dialogue system

A dialogue system and emotion technology, applied in the field of human-computer dialogue in natural language processing, can solve the problems of reduced context relevance and inappropriate emotional expression.

Inactive Publication Date: 2020-10-16
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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AI Technical Summary

Problems solved by technology

However, one problem with increasing diversity is that contextual relevance decreases
In addition, traditional pre-trained word vectors are usually trained by language

Method used

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  • Emotion reply automatic generation method for open domain dialogue system
  • Emotion reply automatic generation method for open domain dialogue system
  • Emotion reply automatic generation method for open domain dialogue system

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Embodiment

[0103] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions will be clearly and completely described below in conjunction with the embodiments.

[0104] Step 1: Build a dialogue corpus, perform word segmentation processing on the input-reply pair (X, Y) in the corpus, and obtain the word sequence of the input and reply sentences, and record the word sequence of the input sentence as X={w 1 ,w 2 ,...,w M}, the word sequence of the reply sentence is recorded as Y={w 1 ,w 2 ,...,w N},w i Represent the i-th word in the sentence, M and N are respectively the number of words contained in the input and reply sentences, in the present embodiment, assume that there is a training sample in the dialogue corpus: (X, Y)=(" guess what ? I have a big news!”, “What is it?”), perform word segmentation processing on it to get input and reply word sequence X={you, guess, what,? , I, have, a, big news! }, Y={is, what,? },...

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Abstract

The invention discloses an emotion reply automatic generation method for an open domain dialogue system, and aims to enable the dialogue system to automatically generate replies rich in content and appropriate in emotion according to input statements of a user. The method comprises the following steps: firstly, preprocessing input and reply statements of each sample in a corpus based on a word embedding table and a VAD sentiment dictionary to obtain an input and reply word embedding sequence and a sentiment embedding sequence; secondly, splicing word embedding and emotion embedding to expand word embedding, introducing replied emotion distribution information into the model, and encoding a spliced sequence in an encoder to obtain input and replied semantic representation vectors containing emotion information; and finally, predicting approximation of conditional prior distribution and posteriori distribution by using semantic representation vectors, sampling latent variables, and reconstructing replies and emotion distribution of the replies through the latent variables. When reply statements are generated, multiple replies are generated through multiple times of sampling, then the sequences are combined with the sequence model and the VAD dictionary, automatic scoring is conducted from the perspective of grammar, semantics and emotion of the replies, and the optimal reply isselected.

Description

technical field [0001] The invention belongs to the field of human-computer dialogue of natural language processing, and in particular relates to an automatic generation method of an emotional reply of an open domain dialogue system based on a deep neural network. Background technique [0002] In recent years, conversational robots have gradually integrated into people's daily life. For example, voice assistants such as Siri, Xiaodu, and Tmall Genie can help people complete some simple tasks through dialogue, such as setting alarm clocks, playing music, and chatting. At present, the existing dialogue systems can be divided into domain-specific dialogue systems and open-domain dialogue systems according to domain knowledge. Domain-specific dialogue systems are limited to background knowledge in a specific domain to conduct dialogues, and related to them are task-oriented dialogue systems, such as movie ticket purchase assistant robots. The open-domain dialogue system has no...

Claims

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Application Information

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IPC IPC(8): G06F16/332G06F16/33G06F40/30
CPCG06F16/3329G06F16/3344G06F40/30
Inventor 刘梦娟包笑明赵培罗莉娟杨云帆
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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