English word spelling system for generating dynamic diagram and word splitting module based on AI

Abstract

The invention relates to an English word spelling system for generating a dynamic diagram and a word splitting module based on AI (Artificial Intelligence), which is used for generating the dynamic diagram matched with English words through the AI and dynamically displaying the relation between word spelling and meanings in a visual manner. According to the English word splitting module, original meaningless letter combinations are divided into a role part and a scene part, and brand new definitions are given to all the letter combinations. By means of the method, complicated word spelling composed of a series of single letters is evolved into story combination of'roles + scenes' formed by combination of several letters rich in meaning, and content input of AI generated diagrams is given. According to the system, a story logic system is provided for word spelling, and the current situation of word spelling visualization deficiency is solved through AI dynamic diagrams. The main purpose is that the English word spelling system is applied to the fields of software and hardware development, education communication and the like.

Description

Technical Field:

[0001] An English word spelling system based on an AI-generated dynamic diagram and word splitting module.

[0002] (1) AI-generated dynamic diagram: Combine the spelling of an English word with its original meaning to form corresponding content input. Generate a dynamic diagram through AI and visually display the connection between the spelling of the English word and its meaning in a dynamic way.

[0003] (2) English word splitting module: A creative invention of the spelling rules of English words. Divide the originally meaningless letter combinations into "role parts" and "scene parts", giving new definitions to each letter combination. Make the complex spelling of English words composed of a series of single letters evolve into a "role + scene" story combination formed by several meaningful letter combinations, and form a relatively stable content output for AI-generated diagrams. Background Art:

[0004] Tens of thousands of English words are composed of 26 letters. Although there are some methods such as word roots to help understanding and memory, the vast majority of English words can be said to have no clear spelling logic.

[0005] Traditional word spelling lacks visual support and mostly relies on syllable combinations. Because there is no necessary connection between the spelling of English words and their meanings, many words can be pronounced but their meanings are unknown. Therefore, in most cases, they can only be memorized by rote.

[0006] This English word spelling system based on an AI-generated dynamic diagram and word splitting module, after stable and operable modular splitting and processing of English word spelling, clearly combines the spelling and meaning of English words, provides a story-based logical system for English word spelling, and solves the current situation of the lack of visual representation of word spelling through AI dynamic diagrams. Summary of the Invention:

[0007] This English word spelling system based on an AI-generated dynamic diagram and word splitting module is characterized in that: for an English word, generate a dynamic diagram through AI. First, by using the original word splitting module, split an English word into a combination of two or more parts with specific meanings, closely combine the meanings of each spelling combination of the English word with its original meaning, form the content input for the corresponding AI-generated picture of the English word, and then use AI to generate a dynamic diagram.

[0008] (1) The system includes:

[0009] (1) AI Image and Video Generation Module: It is used to generate a dynamic diagram combining AI pictures and videos corresponding to an English word according to the input of "character part + scene part" corresponding to the English word and the content of the extended plot.

[0010] (2) English Word Splitting Module: Combining the spelling rules of English words, it creatively defines the meanings of fixed combinations of letters. It defines the combinations of one or several consonant letters as different "character parts", and the combinations of several letters starting with the vowel letters a, e, i, o, u as different "scene parts". Each fixed combination of letters has a fixed meaning. Then, it splits the spelling of the English word into a combination of "character part + scene part" and the extended part, and closely combines the meaning of the spelling combination of the English word with the original meaning of the English word to form the input content for generating the dynamic diagram of the corresponding AI for the English word.

[0011] (3) Interactive Interface: It is used to display the splitting of the English word and the meanings represented by each split part, generate the dynamic diagram of the word with AI, and be associated with the spelling steps in real time.

[0012] (4) Associated Interface: It is used to display the associated words of an English word in the same character but different scenes or different characters but the same scene and the AI dynamic diagrams of the associated words, which is convenient for comparison and distinction.

[0013] (5) Extended Interface: It is used to display the associated words of an English word with different extended plots in the same character and the same scene and the AI dynamic diagrams of the associated words, which is convenient for comparison and memory.

[0014] (6) Reverse Interface: It is used to provide the corresponding AI diagram through the given Chinese words, and use the characters, scenes and extended parts included in the AI diagram to combine into the complete spelling of the English word.

[0015] (2) Example Explanation:

[0016] The combination -ake starting with a vowel letter represents the "cake scene" of cake. What will be the input content of the AI dynamic diagram when different "characters" come to the "cake scene"?

[0017] (1) Using the consonant letter b to represent the bee, "character + scene" is "b-ake baking", then the associated combination of the word bake is "bee - cake - baking", and the AI dynamic diagram will form a video and picture with the content of "the bee's cake is baked by itself".

[0018] (2) Represent the fish with the consonant letter f. "Character + Scene" is "f-ake, forgery, fake". Then the associated combination of the word fake is "fish - cake - fake". The AI dynamic diagram will form a video and picture with the content of "a cake decorated with small fish is a forged fake".

[0019] (3) Represent the lion with the consonant letter l. "Character + Scene" is "l-ake, lake". Then the associated combination of the word lake is "lion - cake - lake". The AI dynamic diagram will form a video and picture with the content of "a lion standing by the lake with a cake in its hand".

[0020] There are also different "characters" such as driver, monkey, jellyfish, queen, rabbit, snake, sheep, etc. facing the "cake scene", which will be combined into drake, make, jake, quake, rake, sake, shake. The AI dynamic diagram will form a series of video and picture combinations corresponding to the content of "character + scene" and the meaning of the word.

[0021] (3) The advantages of this system are as follows:

[0022] (1) The AI-generated diagram is an expression of the meanings of people, objects, places, emotions, states, etc. expressed by specific "characters" contained in English words in specific "scenes", combined with the original meaning of the English word to form a fixed content input. Through the AI-generated dynamic diagram, the connection between spelling and meaning is dynamically displayed in a visual way. It is based on an original "character + scene" splitting module for words, giving a logical system with characters, scenes, stories, and plots to the originally illogical English word spellings. And through a variety of association and extension interfaces, the comparison and distinction of associated, extended, and similar words are strengthened, enhancing understanding and improving efficiency.

[0023] (2) The English word splitting module is a creative invention of the spelling rules of English words. It defines the originally meaningless letter combinations as "character parts" and "scene parts", giving new definitions to each letter combination. It makes the complex English word spellings composed of a series of single letters evolve into a story-based combination of "character + scene" formed by several meaningful letter combinations. The selection of the letter combinations of the "character part" and the "scene part" is defined in principle to be conducive to the display of the story plot and stable output.

[0024] Among them, the "character part" includes:

[0025]

[0026] The "scene part" includes:

[0027]

[0028]

[0029]

[0030]

[0031]

[0032] Description of the Drawings:

[0033] (1) AI Dynamic Illustration Interface: Used to display the splitting of English words and the meanings represented by each split part, generate dynamic illustrations of the words using AI, and be associated with the spelling steps in real time. See all the AI-illustrated words in the attached drawings of the specification. Figures 1 to 22 in the specification.

[0034] (2) Associated Interface: Used to display the associated words and the AI dynamic illustrations of the associated words of a certain English word in different scenarios with the same role or the same scenario with different roles, facilitating comparison and differentiation.

[0035] 1. Word Splitting and AI Illustrations of Different Roles in the Same Scenario:

[0036] (1) Scenario Type 1 - Body Parts, for example: Figure 1 are AI-illustrated words with the "face" as the scenario.

[0037] brace, grace, glace, lace, mace, pace, race, space, trace;

[0038] (2) Scenario Type 2 - Single Object, for example: Figure 2 are AI-illustrated words with the "bell" as the scenario.

[0039] cell, dell, dwell, fell, hell, quell, shell, spell, fellow, mellow, pellet, stellar, smell, swell, well, yell;

[0040] (3) Scenario Type 3 - Specific Location, for example: Figure 3 are AI-illustrated words with the "peak" as the scenario.

[0041] beak,bleak,break,leak,freak,sneak,squeak,teak,weak,steak,tweak,wreak;

[0042] (4) Scene type 4 - Time interval, e.g.: Figure 4 It is an AI diagrammatic word with the "week" as the scene.

[0043] cheek,creek,geek,peek,leek,meek,reek,seek,sleek;

[0044] (5) Scene type 5 - A certain action, e.g.: Figure 5 It is an AI diagrammatic word with the "cheer" as the scene.

[0045] beer, career, deer, jeer, queer, steer, leer, peer, seer, sheer, sneer, veer;

[0046] (6) Scene type 6 - Environment and occasion, e.g.: Figure 6 It is an AI diagrammatic word with the "dream" as the scene.

[0047] beam,cream,gleam,steam,stream,scream,seam,ream,team,preamble,squeamish;

[0048] (7) Scene type 7 - Emotional state, e.g.: Figure 7 It is an AI diagrammatic word with the "need" as the scene.

[0049] bleed,breed,feed,deed,greed,heed,seed,reed,weed,speed,steed,tweed, etc.;

[0050] (8) Scene type 8 - Color feature, e.g.: Figure 8 It is an AI diagrammatic word with the "black" as the scene.

[0051] back,crack,pack,knack, jack,lack,sack,shack,snack,slack,stack,track;

[0052] (9) Scene type 9 - Occupation and position, e.g.: Figure 9 It is an AI diagrammatic word with the "staff" as the scene.

[0053] chaff, quaff, daffy, gaff, faffe, faffer, raffle, raffish, traffic, scaffold, taffy, waffle;

[0054] (10) Scene type 10 - Specific identity, for example: Figure 10 It is an AI-illustrated word with the scene of "dad".

[0055] brad, clad, glad, cad, fad, gad, mad, pad, lad, radar, sad, tad, etc. different types.

[0056] 2. Word splitting and AI illustration of the same character in different scenes:

[0057] (1) Character type 1 - Person, for example: Figure 11 It is an AI-illustrated word with the characters of "queen, king".

[0058] quench, quaff, quell, quest, quern, queer; keel, keen, keep, kernel, keg, ketch;

[0059] (2) Character type 2 - Animal, for example: Figure 12 It is an AI-illustrated word with the characters of "rabbit, pig".

[0060] race, rent, reed, regal, register, reward; pact, perry, perm, pelt, perk, penchant, etc.;

[0061] (3) Character type 3 - Occupation, for example: Figure 13 It is an AI-illustrated word with the characters of "chef, spy".

[0062] chew, chaff, chest, cheek, chafe, chemical; space, speck, speed, speak, spell, spew;

[0063] (4) Character type 4 - Location, for example: Figure 14 It is an AI-illustrated word with the characters of "street, class".

[0064] straddle,strew,steam,strafe,stretch,strength;clad,clever,clench,clergy,clerestory,client;

[0065] (5) Role type 5 - Plants, such as: Figure 15 It is an AI illustrated word with "grass, tree" as the roles.

[0066] greet,grace,grease,greed,grab,grade;tread,treat,traffic,trend,trendy,track;

[0067] (6) Role type 6 - Colors, such as: Figure 16 It is an AI illustrated word with "blue, brown" as the roles.

[0068] bleep,bless,blend,bleed,bleary,bleat;brace,breed,bread,breach,breeze,brew;

[0069] (7) Role type 7 - States, such as: Figure 17 It is an AI illustrated word with "swim, sleep" as the roles.

[0070] sweet,sweat,swaddle,sweep,swear,swell;slack,sleek,sled,sleet,slab,sleazy;

[0071] (8) Role type 8 - Items, such as: Figure 18 It is an AI illustrated word with "glasses, stone" as the roles.

[0072] glee,gleam,glean,glad,glen,glace;steak,steer,stein,stew,steam,stead。

[0073] (III) Extended interface: Used to display related words and AI dynamic illustrations of related words in different extended plots of the same role and the same scenario as a certain English word, facilitating comparison and memory.

[0074] (1) Used to display the comparison of words with similar spellings, such as: Figure 19 It is an AI illustrated comparison of similar words.

[0075] contact / contract; fellow / mellow / yellow; dentist / feminist / pessimist;

[0076] (2) For showing word comparisons of the same characters and the same scenes with different extended parts, such as: Figure 20 、 Figure 21 is an AI diagram comparison showing similar words:

[0077] gaff / gaffe / gaffer; peer / peerage / pioneer; regal / region / register;

[0078] tempt / temple / template / temperature; sextant / sextet / sexton / sextuple.

[0079] (3) For showing the splitting and diagramming of extremely long words to demonstrate the system's advantages, such as: Figure 22 is an AI diagram showing extremely long words:

[0080] cerebrum, cerebellum, destination, vengeance, ketchup, pentagon, dexterous, sergeant, meretricious.

[0081] (4) Reverse interface: Used to provide corresponding AI diagrams based on the given Chinese words, and use the characters, scenes, and extended parts included in the AI diagrams to combine into the complete spelling of English words. Specific implementation method:

[0082] (1) System architecture implementation method:

[0083] 1. Multimodal input module: Supports input methods such as text input and voice input in multiple different languages including Chinese and English. The virtual keyboard supports Unicode multilingual input (Chinese pinyin / English QWERTY / Romanized Japanese). The handwriting recognition engine (LSTM+CTC architecture) supports the recognition of Chinese character stroke order.

[0084] 2. Multilingual processing engine: Fast language feature classification based on FastText (supports 138 languages). Shared encoder (conformer architecture) + language-specific decoder. Dynamic vocabulary switching mechanism.

[0085] 3. Dynamic Diagram Generation Engine: The WebGL technology is used in the 3D modeling unit to build an interactive letter deformation animation. An LSTM network is designed to establish a spatial position memory model for letter sequences. The rigid body dynamics is applied to simulate the process of letter collision and recombination.

[0086] (II) Implementation Modes of Core Algorithms:

[0087] 1. Establish a unique splitting module system for English words, where the specific meanings of different letter combinations correspond to specific diagrams, and establish an association matrix between letter combinations and their meanings.

[0088] 2. Use the improved Delaunay triangulation algorithm to construct a letter space grid.

[0089] 3. Dual-channel Attention Mechanism: The visual focus tracking and the semantic association matrix are updated synchronously.

[0090] (III) Implementation Modes of Interactive Interfaces:

[0091] 1. AR Augmented Reality Module: The SLAM spatial positioning system realizes the fusion of virtual letters and the real environment. The MediaPipe framework is used to implement a library of 26 spelling gestures.

[0092] 2. Multi-dimensional Feedback System. Establish a tactile feedback device and a sound field positioning prompt system.

[0093] (IV) Embodiments of Typical Application Scenarios:

[0094] 1. Special Teaching Aids System: Establish a dedicated compensation model for database training. Develop a multi-sensory collaborative training system.

[0095] 2. Cross-language Learning System: Integrate the etymology database to generate cultural background diagrams.

[0096] (V) Embodiments of Technical Solutions:

[0097] 1. Develop a software and hardware combination that matches and integrates the AI dynamic diagram with the unique English word splitting spelling system.

[0098] 2. Adopt a multi-language input engine to establish an English word spelling system that matches multiple different language systems, including but not limited to Chinese.

[0099] 3. Include but not limited to applying this English word spelling system to fields such as physical teaching, software development, hardware development, international cooperation, and publishing.

Claims

1. (I) Technical field: An English word spelling system based on AI-generated dynamic graphics and word splitting modules. (II) Technical issues: Traditional word spelling lacks visual support, and there is a lack of correlation between the spelling of English words and the meaning they represent. Word spelling lacks a fixed and operational logic, and in most cases can only be memorized by rote. This English word spelling system based on AI-generated dynamic graphics and word splitting modules clearly combines the spelling and meaning of English words after stable and operational modular splitting and processing of English word spelling, providing a story-telling logical system for the spelling of English words, and solving the current problem of lack of visualization of word spelling through AI dynamic graphics. (III) Technical solution: This English word spelling system based on AI-generated dynamic graphics and word splitting modules is characterized by: The dynamic graphics generated by AI completely deconstruct English words. First, by using the word splitting module, an English word is split into 2 or more spelling combinations with specific meanings, and the meaning of each spelling combination of the English word is closely combined with the original meaning of the English word to form the content input of the AI-generated picture corresponding to the English word, and then the dynamic graphics generated by AI are used to realize visual operation. The system includes: (1) AI image and video generation module: used to generate AI dynamic graphics corresponding to English words based on the "character part + scene part" corresponding to the English words and the content input of the extended plot; (2) English word splitting module: Based on the spelling rules of English words, the meaning of fixed letter combinations is defined. The combination of one or several consonant letters is defined as different "role parts", and the combination of several letters starting with vowels a, e, i, o, and u is defined as different "scene parts". Each fixed letter combination has a fixed meaning. Then the spelling of English words is split into a combination of "role part + scene part" and the extended part, and the meaning of the English word spelling combination is closely combined with the original meaning of the English word to form the input content of the AI-generated dynamic graphic corresponding to the English word. (3) Interactive interface: used to demonstrate the decomposition of English words and the meaning of each part, using AI to generate a dynamic graphic of the word and link it with the spelling steps in real time. (4) Associative interface: used to display the associated words of a certain English word in different scenes with the same character or the same scene with different characters, as well as AI dynamic graphics of the associated words, to facilitate comparison and distinction. (5) Extended interface: used to display related words of a certain English word in different extended plots with the same role and the same scene, as well as AI dynamic graphics of related words, to facilitate comparison and memory. (6) Reverse interface: used to provide corresponding AI illustrations based on given Chinese words, and use the characters, scenes and extended parts contained in the AI ​​illustrations to combine into the complete spelling of English words. (IV) Technical Effects: Through AI dynamic graphics and English word splitting modules, a visual and story-telling logical system is provided for the spelling of English words, which closely combines the spelling of English words with their meanings. And through a variety of associations and extended interfaces, the comparison and distinction of associations, extensions and similar words are strengthened, which enhances understanding and improves efficiency.

2. (i) The AI-generated diagram is a combination of the specific "role" contained in the English word in a specific "scene" and the original meaning of the word, forming a fixed content input, and generating dynamic diagrams through AI to dynamically display the connection between the spelling and meaning of the English word in a visual way. It is based on the "role + scene" splitting module of the word, giving the originally illogical English word spelling a logical system with roles, scenes, stories and plots. And through a variety of associations and extended interfaces, it strengthens the comparison and distinction of associations, extensions and similar words, enhances understanding and improves efficiency. (II) The English word splitting module is an invention of the spelling rules of English words. It defines the original meaningless letter combinations as "character parts" and "scene parts", and gives each letter combination a new definition. This makes the complicated English word spelling composed of a series of single letters evolve into a story-telling combination of "character + scene" formed by several meaningful letter combinations. The selection of letter combinations of "character parts" and "scene parts" is defined in accordance with the principle of being conducive to the presentation of the storyline and stable output. (1) The role section includes: (2) "Scene section" includes: (III) Implementation of technical solutions: (1) The user terminal is a touch screen mobile device that supports handwritten spelling input and animation interaction. Develop a software and hardware combination that matches and integrates the English word spelling system based on AI dynamic graphics and word splitting modules. (2) Using a multilingual input engine, establish an English word spelling system that matches a variety of different language systems, including but not limited to Chinese. (3) Including but not limited to applying the English word spelling system to physical teaching, software development, hardware development, international cooperation and publishing.

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