Auxiliary learning method, device and terminal

A learning method and learning state technology, applied in the field of education, can solve problems such as hard to eliminate knowledge blind spots, lack of emphasis, and long time-consuming, so as to save video playback time, improve review efficiency, and prevent the formation of knowledge blind spots.

Inactive Publication Date: 2017-12-01
肇庆高新区长光智能技术开发有限公司
View PDF8 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The embodiment of the present invention provides an auxiliary learning method and device to solve the problems in the prior art that it takes a long time to review the audio and video rec

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
  • Auxiliary learning method, device and terminal
  • Auxiliary learning method, device and terminal
  • Auxiliary learning method, device and terminal

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0091] Such as figure 1 As shown, the embodiment of the present invention provides an auxiliary learning method, including:

[0092] S110: collecting brain waves;

[0093] S120: recording audio and / or video;

[0094] S130: Classify the learning state according to the brain waves, and the learning state includes a low-efficiency learning period and a drowsy period;

[0095] S140: performing speech recognition on the speech in the audio and / or video recorded during the low-efficiency learning period or the dozing period;

[0096] S150: Set a text label according to the voice recognition result;

[0097] S160: Obtain the selection result of the text label and play the audio and / or video corresponding to the time period.

[0098] In an exemplary embodiment, the sampling interval for collecting brain waves is 1 to 3 seconds, and the sampling length is 5 to 10 seconds.

[0099] In a specific implementation process, after the step of recording audio or video, it further includes...

Embodiment 2

[0148] Such as Figure 6 As shown, the embodiment of the present invention provides an auxiliary learning device 2, comprising:

[0149] An acquisition module 210, configured to acquire brain waves;

[0150] Recording module 220, for recording audio or video;

[0151] A grading module 230, configured to classify the learning state according to brain waves;

[0152] The recognition module 240 is used for performing speech recognition on the speech in the recorded audio and / or video during the low-efficiency learning period or the drowsy period;

[0153] Label module 250, is used for setting text label according to speech recognition result;

[0154] The playing module 260 is configured to acquire the selection result of the text label and play the audio and / or video of the corresponding time period.

[0155] In the specific implementation process, such as Figure 6 As shown, the device 2 also includes:

[0156] The time association module 270 is used for associating brain...

Embodiment 3

[0199] Such as Figure 10 As shown, the present embodiment provides an auxiliary learning terminal 3, including:

[0200] Brain wave acquisition component 301 , processing component 302 , memory 303 , camera 304 , audio input component 305 and output component 306 .

[0201] The brainwave collection component 301 can collect brainwave signals and be connected to the processing component. In an exemplary embodiment, the brainwave acquisition component is a ThinkGear AM module or a TGAM module, which acquires brainwaves through the potentials at the forehead electrodes and earlobe. The brain wave signal is captured by the brain wave acquisition component, and after processing, the data such as the brain wave spectrum, the quality of the EEG signal, and the original brain wave are screened out and transmitted to the processing component.

[0202] The processing component 302 is generally used to assist the overall operation of the learning terminal 3, such as operations associa...

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 an auxiliary learning method. The method includes: collecting brain waves; recording audio frequency and/or a video; partitioning levels for learning states according to the brain waves, wherein the learning states include a low-efficient learning period and a sleepy period; carrying out speech recognition on speeches in the audio frequency and/or the video voices recorded in the low-efficient learning period or the sleepy period; setting a text label according to a speech recognition result; and acquiring a selection result of the text label, and playing the audio frequency and/or the video in a corresponding time period. The invention also provides an auxiliary learning device and terminal. According to the method, the device and the terminal, technical problems that in the prior art, consumed time is long and key points are not highlighted when reviewing is carried out through an audiovisual recorded in a classroom, and thus knowledge blind-spots brought when lecture attending efficiency is low are difficult to be eliminated are solved, the reviewing time can be saved, and the key reviewing points can be highlighted.

Description

technical field [0001] The present invention relates to the field of education, in particular to an auxiliary learning method, device and terminal. Background technique [0002] When people are in different states, the frequency of brain waves is also different. According to frequency, brain waves can be divided into delta wave, theta wave, alpha wave, beta wave and so on according to the frequency from low to high. When the alpha band with a frequency of 8-13Hz is the dominant brain wave, the human body enters a state of relaxation and alertness, with highly concentrated mind, good memory and strong creativity, which is the best state for learning. When the β wave with a frequency of 13-25Hz is the dominant brain wave, the human body is in a state of tension. At this time, the classroom atmosphere is often too tense or the pressure is too high, and students feel bored or fearful. At this time, the brain is too excited or tense, it is difficult to concentrate, memory decli...

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): G06F3/01G06K9/00G06F17/30G09B5/06G06Q50/20G10L15/00G10L15/26
CPCG06F3/015G06F16/48G06F16/686G06F16/7867G06Q50/205G09B5/065G10L15/005G10L15/26G06V20/46G06F2218/08
Inventor 吴家隐
Owner 肇庆高新区长光智能技术开发有限公司
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