Unlock instant, AI-driven research and patent intelligence for your innovation.

Human-computer interaction method and system

A human-computer interaction and intent technology, applied in the field of human-computer interaction methods and systems, can solve problems such as inaccurate understanding, and achieve the effects of fast system processing, simple operation, and saving processing time for labeling

Inactive Publication Date: 2019-05-07
ECOVACS COMML ROBOTICS CO LTD
View PDF5 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The technical problem to be solved by the present invention is to provide a human-computer interaction method and system for realizing accurate human-computer communication in view of the inaccurate understanding of user intentions in the existing human-computer interaction technology

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
  • Human-computer interaction method and system
  • Human-computer interaction method and system
  • Human-computer interaction method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0094] The similarity between sentences A and B can be calculated using the following formula:

[0095] sim(A,B)=α*semanticSim(A,B)+β*syntaxSim(A,B)+γ*classSim(A,B)

[0096] Where α+β+γ=1, α>β,γ

[0097] In addition, the neural network can also be used to calculate. After the sentence is vectorized, CNN, RNN or RNN+attention (attention cycle neural network) is used to train the similarity model by calculating the Euclidean distance or cosine angle between two sentences. So as to get the similarity of two sentences. The calculation of this embodiment is simple and easy to explain.

Embodiment 2

[0099] Sentences with the same intent are considered similar sentences, sentences with different intents are considered dissimilar, and the trained model can calculate the similarity between the two sentences.

[0100] The similarity between sentence A and sentence B can be expressed by the following simple formula:

[0101] sim(A,B)=f(Wx1+b,Wx2+b), X1 and X2 are the vectors of sentence A and sentence B respectively, W and b are neural network parameters, and f is the similarity calculated by Euclidean distance or cosine angle degree function. This embodiment requires a large amount of corpus for training, so the accuracy is high.

Embodiment 3

[0103] Sentences and intentions under the same intention are considered similar, and sentences and intentions under different intentions are considered dissimilar. The trained model can calculate the similarity between sentences and intentions.

[0104] The similarity between sentence A and intent C can be expressed by the following simple formula:

[0105] sim(A,C)=f(Wx1+b,Wx2+b), X1 and X2 are the vectors of sentence A and intention C respectively, W and b are neural network parameters, and f is the similarity calculated by Euclidean distance or cosine angle degree function. This embodiment is based on a large amount of corpus training, and the calculation speed is fast, which can effectively improve the response speed of the system.

[0106] The system can use the method of Embodiment 1 to calculate the similarity in the initial stage. After gradually accumulating a large amount of corpus, it can transition to the method of Embodiment 2 or Embodiment 3. When the performanc...

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 provides a man-machine interaction method and system. The method comprises; recognizing voice input information of a user as corresponding user text information; Determining an optimal intention through an intention classifier and corresponding data processing based on an intention tree node group according to the user text information and the intention node label; According to the optimal intention, inquiring a comparison table of the intention and output information to obtain corresponding output information; And outputting the output information. The system comprises a speechrecognition module, an optimal intention determination module, a query module and an output module. According to the method, an intention tree backtracking mechanism is adopted, the user intention recognition accuracy is improved, operation is easy, and system response is rapid.

Description

technical field [0001] The present invention relates to the technical field of automatic response systems, in particular to a human-computer interaction method and system. Background technique [0002] With the development of society, robots that realize various functions play more and more roles in society. In some service industries, friendly and efficient human-computer interaction is particularly important. Among many human-computer interaction methods, such as touch interaction, somatosensory interaction, text mode, voice mode, etc., text and voice are the most common interaction modes. For example, the ATM machine used in the banking system, the credit card machine used in the payment in the retail industry, etc., mostly use text interaction methods to provide accurate question and answer information for human-computer communication. However, compared with the speech method, the text-based human-computer interaction has certain limitations. For example, when the user...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/27G06F40/20
CPCG06F40/20
Inventor 谢韬
Owner ECOVACS COMML ROBOTICS CO LTD