Cross-modal bilateral personalized man-machine social conversation generation method and system

A cross-modal, bilateral technology, applied in the field of bilateral personalized human-computer social dialogue generation, can solve the problem of reducing user experience

Active Publication Date: 2020-11-13
HUNAN UNIV
View PDF6 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] However, in real social interactions between people, both parties can learn each other's personalized information. When replying, the respondent should not only focus on his own personalized expression, but also consider the other party's pe

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Cross-modal bilateral personalized man-machine social conversation generation method and system
  • Cross-modal bilateral personalized man-machine social conversation generation method and system
  • Cross-modal bilateral personalized man-machine social conversation generation method and system

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0049] like figure 1 and figure 2 , The present embodiment bilateral social personalized man-machine dialogue method according to cross-modality generating comprises:

[0050] 1) Code the conversation context E C , Robot personalized information code E T , User personalized information encoding E S , The result of the output result of the last time E prev Performing weighted fusion to obtain weighting fusion coding O enc ;

[0051] 2) Put the weighted fusion O enc , The result of the output result of the last time E prev Bilateral with personalized input model generation decoder, the N best candidate generated Reply List; generating the personalized bilateral models are pre-trained to establish a weighted fusion encoding input encoded output on a time E prev The mapping relationship between the best N candidate reply to the output;

[0052] 3) Calculate the abundance value of each candidate response in the N candidate reply list;

[0053] 4) Select the candidate response of the co...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a cross-modal bilateral personalized man-machine social conversation generation method and system. The method comprises the following steps: performing weighted fusion on a dialogue context code, a robot personalized information code, a user personalized information code and a code of an output result at the previous moment to obtain a weighted fusion code; inputting the weighted fusion code and the code of the output result at the previous moment into a decoder of the bilateral personalized generation model to generate N optimal candidate reply lists, and selecting thecandidate reply with the maximum conditional mutual information abundance value as the final output result. Personalized information is fused in a cross-modal mode, personalized information of figures of two interaction parties is considered, personalized features of the two interaction parties are fully utilized on the premise that reasonable reply content, smooth grammar and coherent logic areguaranteed, and replies which are rich in personality and differ from one another can be generated.

Description

technical field [0001] The invention relates to the technical field based on human-computer interaction, in particular to a method and system for generating a cross-modal bilateral personalized human-computer social dialogue. Background technique [0002] With the advancement of science and technology, human-computer interaction is gradually developing toward intelligence and personalization, and the interaction between humans and robots is getting closer to the interaction between humans in the real world. The traditional human-machine social dialogue generation belongs to the field of natural language processing, which mainly studies the ability of robots to make natural responses according to the user's text input. Different from interpersonal communication, vision is the main sensory source for people to receive external information, and people can make natural and personalized expressions based on external information. Therefore, in order to make the robot more "human-...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F16/332G06N3/04G06N3/08
CPCG06F16/3329G06N3/08G06N3/045
Inventor 李树涛李宾孙斌
Owner HUNAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap