Automatic reply generation method for open domain dialogue system

A dialogue system and automatic generation technology, applied in the field of human-computer dialogue of natural language processing, can solve the problem of lack of semantic information in the reply

Inactive Publication Date: 2019-10-15
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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The reply generation method based on the sequence model finally uses the maximum likelihood estimation method to determine the generated words, which can eas

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  • Automatic reply generation method for open domain dialogue system
  • Automatic reply generation method for open domain dialogue system
  • Automatic reply generation method for open domain dialogue system

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[0084] Example

[0085] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the following describes the technical solutions clearly and completely in conjunction with the embodiments.

[0086] Step 1: Construct a dialogue corpus. Each sample in the corpus is composed of a user input sentence and a user reply sentence, denoted as {(X 1 ,Y 1 ),(X 2 ,Y 2 ),…,(X N ,Y N )}; In this embodiment, it is assumed that there is a training sample in the dialogue corpus: (X, Y) = ("Good morning!", "Morning, have you had breakfast?"), where "Good morning!" is The input sentence, "Early, have you had breakfast?" is the reply sentence; first, the input sentence X and the reply sentence Y are segmented to obtain the word sequence {"morning", "好", "!"} and the reply of the input sentence X The word sequence of sentence Y {"Morning", ",", "Eat", "Breakfast", "La", "Do you", "?");

[0087] Then use the general word vector table to transform each word in...

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Abstract

The invention discloses an automatic reply generation method for an open domain dialogue system, and aims to enable the dialogue system to automatically generate a reply statement which conforms to semantics and contains information quantity according to an input statement of a user. The method comprises the following steps: firstly, constructing a dialogue corpus, preprocessing input and reply statements of each sample to obtain word vector sequences of the input and reply statements, and respectively inputting the word vector sequences into two encoders to obtain semantic representation vectors of the input and reply statements; secondly, retrieving knowledge graphs containing entity words in a knowledge base according to the entity words contained in the input statement, and calculatinga vector of each knowledge graph; thirdly, fusing the knowledge graph vector with the semantic representation vectors of the input statement and the reply statement through two fusion networks, and inputting the fused vectors into a decoder to generate the reply statement; fourthly, training a reply automatic generation model based on a corpus; and finally, for a new input statement, utilizing the reply automatic generation model to generate a reply.

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 reply generation method of an open domain dialogue system based on a deep neural network. Background technique [0002] Human-computer dialogue systems can be divided into closed-domain dialogue systems and open-domain dialogue systems according to different application fields. Closed-domain dialogue systems usually have clear goals and limited knowledge scope, and only generate responses to domain-specific user input, for example, dialogue systems for airline ticket reservations and restaurant order dialogue systems. Open-domain dialogue systems usually have no clear goals and limited knowledge scope. Users and the system can have free dialogues on any topic, such as chatting robots, as chat partners, can freely chat with users. attached figure 1 A diagram showing a conversation between a person and a chatbot. The ...

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Application Information

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IPC IPC(8): G06F16/33G06F16/332
CPCG06F16/3329G06F16/3344
Inventor 刘梦娟孟园赵培包笑明刘瑶
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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