TWI742232B - Method of learning language - Google Patents

Abstract

A method of language learning that allows users to understand the words through learning different related words or phrases in an interactive way, including through the sentences. For example, to learn the meaning of "apple", including some related words, such as through the word of "fruit", to understand that "Apple" is a "fruit". Through the word of "tree" and their relationship to understand that "Apple" grows on the "tree". Therefore, this invention enables users to learn each words and phrases through various words in different relationships and orders, to train children in developing language comprehension and logic thinking.

Description

Methods of language learning

The present invention relates to a method of learning Chinese, and this method needs to be executed with a computer.

Regarding the way of teaching children to learn Chinese, for example, US Patent US7563099 Multi-media method and apparatus for teaching language (Multi-media method and apparatus for teaching language) reveals that a series of images about an object are displayed. These images include different But comparable objects can also be accompanied by voice instructions to explain these objects. Such teaching can increase the impression of the objects.

US Patent US 7933852 Method and Apparatus for Developing Cognitive Skills (Method and apparatus for developing cognitive skills) By displaying images, users are asked to answer the images, and the images can be repeatedly displayed to help students understand cognitive skills.

However, for the understanding of cognitive ability, the previous proposal did not allow users to understand the word or word they want to learn from different words or words in an interactive way. For example, to understand "table", you can understand "table" from "wood". "Material" can use "wood"; "chair" can also be used to understand "table", because "chair" is often used with "table"; or "table" can be understood from "desk lamp" because "desk lamp" is often used put it on the table.

None of the previous proposals have provided users with ways to interact with different objects such as text, images, and sounds through the learning methods of understanding the above knowledge to help students' cognitive ability and understanding of the logical connection between words and sentences.

The main purpose of the present invention is to provide a language learning method that allows users to understand the word or word they want to learn from different words or words in an interactive way, including through sentences. For example, if you want to learn the meaning of "apple", including through To learn some related words, such as understanding "apple" through the relationship between "fruit" and "apple", then you can understand that "apple" is a kind of "fruit". Another example is to understand that "apples" grow on "trees" through the relationship between "trees" and "apples". Therefore, the design of the present invention allows users to recognize characters or words from a different perspective, and can also train children to think differently.

In order to achieve the above objective, the present invention provides a method of language learning. First, a main object (such as Apple) and at least one related object are displayed on the screen, and a plurality of related objects are preferably displayed. A plurality of related objects can surround the main object, for example. Objects can be text or images, or text and images.

When the user selects a related object, a combined sentence is selected. This combined sentence includes the text of the main object (such as Apple) and the text of the related object (such as Fruit). The combined sentence is, for example, Apple is a fruit.

According to one embodiment, the main object, related objects, and combined sentences are displayed, so that the user can understand the main object through the related objects and combined sentences.

If the user selects a related object (such as Fruit), then a new main object (such as Fruit) is generated, and a new related object is also generated. With this continuous generation of new main objects and new related objects, users can gradually learn more words, words and sentences according to their interests, and gradually extend the learning from related objects, that is, Each user can learn according to his own interest, his own level, and his own pace. The present invention is suitable for each user through the generation of dynamic content.

In the present invention, a database is needed to operate, and the database can be continuously updated. It is best to introduce big data analysis to calculate the relevance of each object, or the weight of each object in the composite sentence, etc., so that the present invention is learning. Can get smarter and smarter.

According to an embodiment of the present invention, a movie can also be put in. After the movie is played, a plurality of candidate host objects can be displayed so that the user can select one of them as the host object, so that the user can touch the picture, sentence, and Can learn through videos.

According to an embodiment of the present invention, interactive question and answer can also be put in. After each user gradually extends the learning from the related objects according to his own interest, degree, and pace, the present invention records the single or multi-layer related objects learned by the user to provide learners with repeated exercises and interactive question and answer content. Interactive question and answer can understand the user's cognitive ability of different objects such as text, image, voice, etc., and can also test whether learners understand the logical connection between words and sentences.

1: computer

10: Near-end computer

11: processor

12: Memory

13: screen

14: Horn

15: Input device

15m: microphone

16: Communication device

20: remote server

21: processor

22: Memory

26: Communication device

30: Language learning software program

30s: language learning software program

31: Database

31s: database

31a: text

31b: related words

31c: words

31d: Degree

31e: Number of learning

31f: Voice file

31g: image file

31h: video file

31i: video tag

31j: weight

31k: Association

41: The first main object

41t: the first main text

41g: the first main image

41v: Movie

43: The first related object

43t: the first related word

43g: The first related image

43a: The first target related object

45: The first combination of words

45a: The first combination alternative sentence

45b: The second combination alternative sentence

47: The second main object

47t: the second main text

47g: second main image

49: The second related object

49t: The second related word

49g: second related image

50: Candidate main object

50t: Candidate main object term

51: Compare the target image

51a: Corresponding image

51b: Candidate image

51c: Candidate image

51d: Candidate image

51e: Candidate image

71: First choice instruction

72: second choice instruction

73: Third selection instruction

74: Fourth selection instruction

75: Fifth selection instruction

76: Sixth selection instruction

80: Movie

90: User

95: Network

131: The first display interface

132: The second display interface

133: The third display interface

134: The fourth display interface

135: Fifth display interface

136: The sixth display interface

Figure 1 is a diagram of the hardware architecture of the present invention.

Figure 2 is a flow chart of the present invention.

Fig. 3 is a schematic diagram of the process of generating various objects according to the present invention.

Fig. 4 is a schematic diagram of the process of generating instructions of the present invention.

Fig. 5 is a schematic diagram of the database of the present invention on the near-end computer.

Fig. 6 is a schematic diagram of the database placed on the remote server according to the present invention.

FIG. 7 is a schematic diagram of the first display interface of the present invention.

Fig. 8 is a schematic diagram of the present invention regarding the film.

FIG. 9 is a schematic diagram of the second display interface of the present invention.

FIG. 10 is a schematic diagram of the third display interface of the present invention.

FIG. 11 is a schematic diagram of the present invention regarding the related object becoming the new main object.

FIG. 12 is a schematic diagram of the conversion process of each display interface of the present invention.

FIG. 13 is a schematic diagram of the first embodiment of the fourth display interface of the present invention.

FIG. 14 is a schematic diagram of the second embodiment of the fourth display interface of the present invention.

FIG. 15 is a schematic diagram of the fifth display interface of the present invention.

In order to allow your reviewer to better understand the technical content of the present invention, preferred specific embodiments are described as follows.

Please refer to FIG. 1 for the hardware architecture diagram of the present invention. In this embodiment, the computer 1 includes a near-end computer 10 and a remote server 20. In this embodiment, the near-end computer 10 is, for example, a tablet or smart phone that is popular now. The near-end computer 10 includes a processor 11, a memory 12, a screen 13, a speaker 14, an input device 15 (such as a microphone 15m) and a communication device 16 (such as wifi). The input device 15 is a microphone, or a touch module combined with the screen 13, a mouse, or a keyboard, etc., and the memory 12 stores the language learning software program 30 (such as App) of the present invention.

The remote server 20 includes a processor 21, a memory 22 and a communication device 26. The memory 22 stores a language learning software program for 30s. The remote server 20 is connected to the communication device 16 of the near-end computer 10 through the communication device 26 and the network 95.

In this embodiment, the computer 1 includes a structure of a near-end computer 10 and a remote server 20. The remote server 20 basically serves a plurality of near-end computers 10. The work of the near-end computer 10 and the remote server 20 can be designed in different ways. For example, almost all operations are performed on the remote server 20 or are concentrated on the near-end computer 10. For example, the remote server 20 is only responsible for updating the database of the near-end computer 10, member registration, or collecting the usage behavior of the near-end computer 10. The other methods of the present invention regarding language learning are all completed on the near-end computer 10, and the database is in the near-end computer 10. It is best to have both the end computer 10 and the remote server 20, but generally speaking, the database of the remote server 20 is usually relatively complete and complex. For example, the database of the remote server 20 includes managing the use of different local computers 10 , Or some different fields in order to enter the smart calculation, or to collect user data. It should be noted that the definition of computer 1 in this specification can also include only the near-end computer 10 without the remote server 20, and the near-end computer 10 executes all the calculation processes of the present invention; the definition of computer 1 in this specification also It may only include the remote server 20, and the remote server 20 executes all the calculation procedures of the present invention and is used in an interactive manner via the near-end computer 10. Therefore, the language learning method of the present invention is implemented through the processor 11 (may also include the processor 21) to execute the language learning software program 30 (also may include the language learning software program 30s), regarding the local computer 10 and the remote server 20 The structure of this is a conventional technology, so I won’t repeat it here.

Hereinafter, please refer to FIG. 2 for the flowchart of the present invention, and please also refer to FIGS. 3 to 15. For the sake of clear description, the left block in Figure 2 is the processing flow, and the right block is the output flow.

Step 201: Select a first master object 41 from a database 31 or database 31s.

Step 202: Select at least one first related object 43 from the database 31 or the database 31s. Please refer to Figure 5~Figure 7. In this embodiment, the database 31 is placed in the memory 12 of the near-end computer 10, and the database 31s is placed in the memory of the remote server 20. In the memory body 22, the data stored in the database 31s is usually relatively complete. It should be noted that the database can also only be placed on the local computer 10 or the remote server 20. For example, when the computer 1 does not include the remote server 20, there will be no database 31s, but the data of the local computer 10 The database can be a relatively complete database such as database 31s. This kind of resource allocation may have different methods for the convenience of management. This is a well-known technology, so I will not repeat it here. In this embodiment, the database 31 has fields such as text 31a, related words 31b, words and sentences 31c, degree 31d, number of learning 31e, voice file 31f, image file 31g, video file 31h, and video tag 31i. Because Figure 5 cannot fit all the fields, Figure 5 mainly shows schematic diagrams of fields 31a~31i. The database 31s in this embodiment has text 31a, related words 31b, words and sentences 31c, degree 31d, learning times 31e, weight 31j, and association 31k. Among them, the weight 31j is calculated by calculating the frequency of plural words 31a and plural related words 31b used together in the database 31s, and the highest frequency is set as the largest weight, and the word with the most weighted word is regarded as the first Related objects 43. Among them, the association 31k is to record the logical relationship between the text 31a and the related word 31b in the sentence 31c of the database 31s, including: Relate (relation), ls-A (is one), Property (attribute), Location (location), Purpose and so on. Because Figure 6 cannot fit all the fields, the 31f~31i fields are not shown in Figure 6. Figure 6 mainly shows the schematic diagram of the fields 31a~31e and the display fields 31j and 31k. Figures 5 and 6 only show a very small part of the database 31 or the database 31s. The database 31 or the database 31s is only an embodiment. The database 31 or the database 31s can store field elements in various ways. Many architectures.

Step 203: Display the first main object 41 and at least one first related object 43 on a first display interface 131. Please refer to Figure 7. In this embodiment, the first main object 41 is "Apple", and there are six first related objects 43, namely "Fruit", "Tree", "Banana", "Eat", " House","Computer". The "things" mentioned in this manual Pieces can include one of "images" or "texts", or "images" and "texts". As shown in Figure 7, "objects" include "images" and "texts." For example, the first main object 41 includes a first main text 41t and a corresponding first main image 41g, and each first related object 43 includes a first A related word 43t and a first related image 43g.

Each text has a corresponding voice file 31f, image file 31g, and video file 31h, so that the image, voice, video, etc. of the object to be displayed later can be found. Of course, if the voice is text to speech via software, a voice file is not required. In addition, when the first main object 41 appears, the first main text 41t is voiced through the speaker 14.

The first display interface 131 places the first main object 41 in the center, and six first related objects 43 surround the first main object 41, so that the user 90 (especially suitable for children or English beginners) can understand The theme is the first main object 41 (Apple), and the words and sentences related to the theme are the six first related objects 43 surrounding it.

There are many ways to select the first main object 41 in step 201, such as sorting or random, or the user 90 designates the first main object 41 through the input device 15. The input device 15 can be a keyboard, a microphone or a touch Modules, etc., for example, the user 90 speaks "Apple" through the microphone, so that the language learning software program 30 can select the first host object 41 from the database 31 and so on.

The first related object 43 selected in step 202 can also be specified by the user 90 in various ways. Another way is to select the first related object 43 related to the first main object 41 from the database 31. For example, "Apple" is selected as the first main object 41 as an example. Please refer to Figure 5. "Apple" corresponds to many related words 31b, such as "Fruit" and "Tree", etc., so the first related object 43 can be connected from Choose among the words 31b. For example, there are 200 related words 31b corresponding to "Apple", select six The method of the related word 31b can be random, or based on the fields of "Level 31d", "Number of Learning 31e" or "Weight 31j" as a reference.

Each "character sentence 31c" has a corresponding record of "weight 31j", "relevance 31k", "degree 31d", and "number of learning 31e". The words recorded in the "character sentence 31c" column all contain the word 31a( The first main text 41t, such as Apple), and related words 31b, such as "Apple is a fruit" means "Apple" and "frut", and associated 31k records the relationship between "Apple" and "fruit":" ls-A". If "weight 31j" is used as the basis for selecting "connected words 31b", for example, the higher the "weight 31j" corresponding to "word sentence 31c", the more related it is to "Apple". For example, "Apple is a fruit." has a weight score of "8", which means that the word "Apple is a fruit." has a high probability of being used, so it indirectly also represents a high connection between "fruit" and "Apple". Therefore, it should be prioritized to single out "fruit" as the first related object 43. The score of "weight 31j" can actually be calculated through big data analysis. The easier the sentence is used, the higher the score of "weight 31j".

The meaning of "Level 31d" represents the degree of difficulty of "Sentence 31c". For example, the longer the sentence "Level 31d" is, the more difficult it is, or the higher the difficulty of "Text 31a", it will also affect "Level 31d". And "the number of learning times 31e" is the number of times each "word sentence 31c" is displayed or learned. Therefore, the first related object 43 can also refer to "Level 31d" or "Number of learning 31e" as a choice. For example, beginners can consider "Level 31d", or "Number of learning 31e" is too many, and it will no longer be the number one. Related objects 43, for example, "Apple is a fruit." has been learned 3 times, then "fruit" is no longer selected as the first related object 43.

Step 204: Receiving a first selection instruction 71 forms a first target-related object 43a. For example, the user 90 looks at the first display interface 131 displayed on the touch screen 13 (assuming that the local computer 10 is a flat panel), and clicks on the first link "Fruit" by hand Object 43, the first related object 43 of "Fruit" is the first target related object 43a. That is, when user 90 is learning "Apple", he wants to know the relationship between "Apple" and "Fruit". In addition, when the first related object 43 is selected, the first related word 43t can also be spoken out through the speaker 14. An important feature of the present invention is that when learning a word (such as Apple), it includes understanding Apple through other words (such as Fruit). For example, the user 90 clicks on "Tree" to understand the relationship between "Apple" and "Tree". This kind of understanding of a word through different words can produce multiple angles or multiple levels to understand a word, and it will make it easier The user 90 thus extends to understand other words and sentences.

Step 205: Select a first combination sentence 45 from the database 31 or the database 31s. The first combination sentence 45 includes the first main text 41t and the first related word 43t of the first target related object 43a. For example, "Fruit" becomes the first target related object 43a, and the related words and phrases 31c of "Apple" and "Fruit" have "Apple is a fruit." and "Apple is a kind of fruit." Choose at least one word sentence, you can choose randomly or according to the weight 31j, the degree 31d, or the number of learning 31e, or choose the plural number sentence. For example, the choice is based on the higher weight, and the first combination sentence 45 is "Apple is a fruit.".

Step 206: On a second display interface 132, the first main object 41 (Apple), the first target-related object 43a (fruit), and the first combination sentence 45 ("Apple is a fruit.") are displayed. Please refer to FIG. 9, the second display interface 132 allows the user 90 to learn the relationship between the first main object 41 (Apple) and the first target-related object 43a (fruit) through the first combination sentence 45 ("Apple is a fruit.") ’S association. In a preferred embodiment, in addition to displaying the first combination sentence 45 ("Apple is a fruit."), the first combination sentence 45 is also spoken out through the speaker 14. Of course, you can also use the speaker 14 to connect the first group The compound sentence 45 is uttered in a phonetic manner, and the first compound sentence 45 is not displayed. It should be noted that in the embodiment, the first main object 41 (Apple) and the first target-related object 43a (fruit) are both displayed, but they may not be displayed.

In addition to displaying the first combined word sentence 45, the first combined alternative sentence 45a may also be displayed. The first combined alternative sentence 45a includes the corresponding text 43t of the first target-related object 43a. The original first main text 41t (Apple) is replaced with other words. The first combined alternative sentence 45a is "Banana is a fruit. ", the first combination sentence 45 and the first combination alternative sentence 45a have a common connection and sentence pattern, so that children can understand the meaning of "is a" or be familiar with the structure of the sentence. Or replace the first main text 41t (Apple) with other related words (Computer), the second combination alternative sentence 45b is "Apple computer is great.", the first combination sentence 45 and the second combination alternative sentence 45b have The same association or weight, so that children can understand (Apple) can represent objects with different meanings.

Step 207: Receive a second selection command 72 (for the first main object 41), please refer to FIG. 9. If the user 90 continues to select the first main object 41 (such as Apple), for example, by clicking on the touch screen 13, or by voice Say "Apple" through the microphone 15m to choose. At this time, it will return to the first display interface 131 (FIG. 7).

Step 208: Receive a third selection instruction 73 (for the first target-related object 43a) to form a second main object 47. Please refer to FIG. 9. If the first target-related object 43a (such as Fruit) is selected, the first target-related object 43a will become the new main object: the second main object 47.

Step 209: At least one second related object 49 is selected from the database 31. Step 209 actually has the same meaning as step 202. When the new main object comes out, it must be targeted at the new main object. Select the corresponding related object from the selected item. Since the second main object 47 is "Fruit", the related object of "Fruit" must be selected. In this embodiment, five second related objects 49 are selected, such as "Table", "Egg", "Mango", "Apple", "Banana", please refer to step 202 for the description of step 209.

Step 210: Please refer to FIG. 10, the third display interface 133 displays the second main object 47 and at least one second related object 49. Similarly, the second main text 47t and the second main image 47g of the second main object 47 are displayed, and the second related words 49t and the second related image 49g of each second related object 49 are also displayed. The procedure of step 210 is actually the same as that of step 201.

According to the flow explained above, FIG. 11 shows one of the important features of the present invention. The center circle represents the main object, and the surrounding circles represent related objects. Each related object can form a new main object and develop a new related object. For example, in the group A (such as Apple), because the related object is selected (step 204), after learning the compound sentence, the new main object can be formed by clicking the related object, so for example, A1 (such as Fruit), A2( Such as Eat), A3 (such as Tree). For example, the group A3 has developed A31 (such as Banana) and A32 (such as House) because the related objects are selected. And A32 can develop A321 (such as Computer). With this continuous generation of new main objects and new related objects, users can gradually learn more words and characters according to their interests, and the related objects gradually extend their learning, that is, each user can follow his own Interests, one's own level, one's own pace to learn, the present invention is suitable for each user through the generation of dynamic content.

In order to increase the fun of children's language learning, the above process can be combined with the video. Please refer to FIG. 12 for the flow diagram of each display interface conversion after matching the video, and also refer to FIG. 8, FIG. 13, and FIG. 14.

Step S11: A video 80 can be played at the beginning.

Step S12: When the video 80 is played or after playing, the fourth display interface 134 can display a plurality of candidate main objects 50 and candidate main object words 50t. The user 90 selects the object he likes to learn, for example, the user 90 selects the object "Apple" in the video 80, so the language learning software program 30/30s accepts the second selection command 72.

There are many ways to select multiple candidate host objects 50. For example, referring to Figure 5, each text has a corresponding video, which is recorded in the video file 31h, and each video can record a video tag 31i. For example, as shown in Figure 13, it is based on "Apple "Corresponding to the video tag 31i, six candidate main objects 50 of Apple, Fruit, House, Table, Banana, and Computer are displayed. Of course, the candidate main object 50, the word 50t can also be automatically obtained by analyzing the subtitles or video images of the video. Basically, the candidate main object 50, the word 50t should preferably appear in the video, so that after the child has watched the video, the fourth display interface 134 displays these candidate main objects 50. The word 50t allows the child to choose when he just saw the video. Objects that are of interest, or objects that you don’t understand, will enhance the effect of video learning.

Step S13: At this time, it switches to the first display interface 131, as shown in FIG. 7, "Apple" becomes the first main object 41.

Step S14: After the user selects the related object, he can enter the second display interface 132. The second display interface 132 mainly learns the relationship between the main object and the related object. The second display interface 132 can also return to the first display interface 131/the third display interface 133. For the description of step S13 and step S14, please refer to the description of the flow in FIG. 2 above.

Step S15: If the user clicks to play the video on the fourth display interface 134 (as shown in Figure 13), the language learning software program 30/30s accepts the fourth selection command 74 and plays the video 41v "Fruit".

Step S16: When or after the video 41v is played, the fifth display interface 135 is displayed, please refer to FIG. 14. Please also refer to the description of step S16 for this part. The fifth display interface 135 displays plural candidate host objects 50 and words 50t after the video is played. Please refer to Figure 14, the user 90 selects the object he likes to learn, for example, the user 90 selects the object "Fruit", so the language learning software program 30/30s accepts the third selection command 73, and then enters the third display interface 133 , As shown in Fig. 10, "Fruit" becomes the second main object 47. If the user clicks on the video to play, the language learning software program 30/30s accepts the fourth selection command 74 and plays the video 41v "Apple" (Figure 8).

The above steps S11 and S12 in FIG. 12 are only the initial steps, so they are represented by dashed squares, and then steps S13 to S16 are schematic diagrams of the interface conversion after the user starts learning. For example, the user 90 can choose to return to the first display interface 131 and the second display interface 132, learn to learn sentences and characters, or continue to learn from playing different videos 41v.

Please also refer to FIG. 3, which shows how the above-mentioned objects (such as the first main object 41, the second related object 49, etc.) are generated are not limited to one method, for example, after voice input, the voice is then converted to text; Either input via keyboard/mouse; or input via touch with the touch screen; or select the software with the database, as explained in the above steps; or after playing the video, analyze the video subtitles, voice or Image, or check the field of the video tag 31i in the database.

The present invention generates new main objects and new related objects according to Fig. 11 (please refer to Figs. 4, 7, 9, and 10 together). The user gradually extends to learn more words and characters, and selects commands 71~ 75 The selected single-layer or multi-layer main objects and related objects are recorded to provide learners with the content of repeated practice. These internal objects can also be recorded. Allows interactive Q&A with users for text, image, and voice comparison. Please refer to Figure 15 together, for example, record the first main object 41, related objects 43, words and sentences 45, second main object 47, second related objects 49, combined alternative sentences 45a, 45b, etc. that the user has learned, and A sixth display interface 136 displays a main object randomly selected from the recorded content as the comparison target image 51, and the interaction is completed by receiving a fifth selection instruction 75 from the user; in other words, as After receiving a sixth selection instruction 76, one can enter a first display interface 131 and a second display interface 132 or other display interfaces to continue learning different objects. Figure 15 shows the comparison target image 51 at the upper left, and the user is asked to select one of the four candidate images 51b, 51c, 51d, 51e from the bottom as the image most related to the comparison target image 51 to correspond to Image 51a.

Please also refer to Figure 4, about the selection commands 71~76 can also be generated in various ways, for example, the user 90 uses voice, keyboard/mouse, or with the touch screen to input through touch, which can be generated after 15m through the microphone Select commands 71~76.

It should be noted that many of the above-mentioned embodiments are given as examples for the convenience of description, and the scope of rights claimed in the present invention should be subject to the scope of the patent application, rather than being limited to the above-mentioned embodiments.

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Claims (11)

A method of language learning used on a computer by a user (90). The computer (10) includes a processor (11), a memory (12), a screen (13) and a speaker (14), wherein the memory (12) includes storing a language learning software program (30), the language learning software program (30) includes a database (31), and the method executes the language through the processor (11) Learn the software program (30) to achieve the following steps: select a first master object (41) from the database (31), wherein the database (31) includes a first master object (41) corresponding to the first master object (41) Text (41t) and a first main image (41g), and the first main image (41g) is the representative image of the first main text (41t); displaying the corresponding first main object (41) The first main text (41t) or the first main image (41g) is on the screen (13); at least one first related object (43) is selected from the database (31), wherein the database (31) ) Includes a first related word (43t) corresponding to the at least first related object (43) and a first related image (43g), and the first related image (43g) is the at least one first related A representative image of the word (43t); displaying the first related word (43t) or the first related image (43g) corresponding to the at least one first related object (43) on the screen (13); Select a first combined sentence (45) from the database (31), the first combined sentence (45) including the first main text (41t) and the first related word (43t); and display the first The combined word sentence (45) is on the screen (13), or the first combined word sentence (45) is spoken through the speaker (14). For the language learning method described in claim 1, wherein the at least one first related object (43) is a plurality of first related objects (43), which further includes receiving a first selection instruction (71), The first selection instruction is determined by the user (90) from a plurality of A related object (43) selects one of them to be the basis for selecting the first combined word (45), and the selected first related object (43) forms a first target related object (43a). The method of language learning as described in item 2 of the scope of patent application, wherein the first main object (41) is displayed and a plurality of first related objects (43) are displayed on the screen (13) in a first display interface (131) display, and the display of the first combined word (45) is displayed on a second display interface (132) on the screen (13), wherein the second display interface (132) further includes displaying the first main The object (41) and the first target-related object (43a) further include receiving a third selection instruction (73), the third selection instruction being used by the user (90) from the second display interface (132) The first target-related object (43a) is selected so that the second display interface (132) is converted to display a third display interface (133), wherein: the first target-related object (43a) forms a second main object (47) ), the third display interface (133) displays the second main object (47); selects at least one second related object (49) from the database (31), wherein the database (31) includes the at least second The related object (49) corresponds to a second related word (49t) and a second related image (49g), and the second related image (49g) is a part of the at least one second related word (49t) Representative image; the third display interface (133) displays the second related word (49t) or the second related image (49g) corresponding to the at least one second related object (49). The language learning method described in item 3 of the scope of patent application further includes receiving a second selection instruction (72), and the second selection instruction is generated by the user (90) from the second display interface (132) The first main object (41) is selected, so that the second display interface (132) is converted to display the first display interface (131). The language learning method described in claim 4, wherein the second display interface (132) further displays a first combined alternative sentence (45a), and the first combined alternative sentence (45a) includes the first target The corresponding text of the related object (43a), the first combined word sentence (45) and the first combined alternative sentence (45a) have a common connection and sentence pattern. The language learning method described in item 5 of the scope of patent application, wherein the second display interface (132) further displays a second combined alternative sentence (45b), and the second combined alternative sentence (45b) includes the first main text (41t) corresponding to the first related word (43t), the first combined word sentence (45) and the second combined alternative sentence (45b) have a common association and weight. For example, the language learning method described in item 2 of the scope of patent application, wherein the selection of the first main object (41) is generated by analyzing the voice uttered by the user, the plural first related objects (43) or the first A selection command (71) is generated by analyzing the voice uttered by the user. The language learning method described in item 2 of the scope of patent application, wherein the first main object (41) is generated based on a film (80), and a plurality of candidate main objects (50) are generated according to the film (80) , And a fourth display interface (134) displays the candidate main object (50), and the first main object (41) is selected by receiving a second selection command (72) of the user, and a plurality of The candidate host object (50) is generated by analyzing the subtitles of the film (80), analyzing the voice of the film (80), or generated based on the plural video tags recorded in the film (80); it also includes playing The movie (41v), and after the movie (41v) is played, generate a plurality of candidate master objects (50) based on the movie, and display the plurality of candidate master objects (50) by a fifth display interface (135) , And a second main object (47) is selected by receiving a third selection command (73) of the user; such as continuing to play the video (41v) is selected by receiving a fourth selection command (74) of the user Selected. For example, the method of language learning described in item 1 of the scope of patent application, wherein the database (31) has a corresponding weight for recording the first compound sentence (45), so that when the first compound sentence (45) is selected, it will be Refer to the weight. For example, the method of language learning described in item 2 of the scope of patent application, which further includes using different categories, selecting one or more main objects (41), selecting one or more related objects (43), Choose one or plural combination sentences (45), etc. to form the learning content of different topics for users of different levels (90). For example, the method of language learning described in item 1 of the scope of patent application, which also includes recording the main objects (41), related objects (43), and combined words (45) that the user (90) has learned to provide The content of the learner’s repeated exercises is also compared and interacted with text, images, and voices; and a sixth display interface (136) displays the comparison target image (51), and the interaction is received by the user One of the fifth selection instructions (75) from a plurality of candidate images (51b), (51c), (51d), (51e), select one of them as the most relevant corresponding image for the comparison target image (51) Like (51a); if a sixth selection instruction (76) is received, the user (90) can continue to learn different objects.

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