CN112748811A - English word input method and device - Google Patents
English word input method and device Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/02—Input arrangements using manually operated switches, e.g. using keyboards or dials
- G06F3/023—Arrangements for converting discrete items of information into a coded form, e.g. arrangements for interpreting keyboard generated codes as alphanumeric codes, operand codes or instruction codes
- G06F3/0233—Character input methods
- G06F3/0237—Character input methods using prediction or retrieval techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/90335—Query processing
- G06F16/90344—Query processing by using string matching techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/205—Parsing
- G06F40/216—Parsing using statistical methods
Abstract
The method comprises the steps of obtaining an input letter string, segmenting the letter string to obtain at least one segmentation result, wherein the letter string comprises at least three letters, when the segmentation result is inquired to have at least one syllable combination corresponding to the syllable combination in a database, traversing all words stored in the database according to the syllable combination, adding the words into a first candidate word list when the words are judged to meet the syllable combination, storing the first candidate word list into the database, calculating the word frequency of the words in the first candidate word list to generate a second candidate word list, and determining a target word corresponding to the letter string based on the second candidate word list. The application also provides an English word input device, which improves the intelligent induction degree and reduces the difficulty of inputting English words by users, thereby achieving the purpose of inputting required English words quickly and accurately.
Description
Technical Field
The application belongs to the technical field of letter input methods, and particularly relates to an English word input method and device.
Background
At present, english words or english reading materials and the like are increasingly common in daily life of people, when english is input on computer equipment, the english can be directly input through a keyboard, a virtual keyboard displayed on a touch screen and the like, and generally 26 letters correspond to 26 letters on an input keyboard one by one. In the process of inputting words, most people generally adopt various input methods, and if the input methods are not used, complete words need to be input, but if full-text search is used for the words, search results are too many, and it is tedious for a user to spend a large amount of time to search for target words, so that the whole English words cannot be quickly input, even the efficiency of inputting English by the user is influenced, and the difficulty of inputting English words by the user is increased.
Disclosure of Invention
The embodiment of the application provides a word input method and a word input device, which can solve the problem that a user cannot input words quickly and accurately because the user forgets to spell the words in the process of inputting English words.
In a first aspect, an embodiment of the present application provides an english word input method, including:
acquiring an input letter string, and segmenting the letter string to obtain at least one segmentation result, wherein the letter string comprises at least three letters;
when the segmentation result is inquired to have at least one syllable combination corresponding to the database, traversing all words stored in the database according to the syllable combination;
when the word is judged to meet the syllable combination, the word is added into a first candidate word list, and the first candidate word list is stored in the database;
and calculating the word frequency of the words in the first candidate word list to generate a second candidate word list, and determining a target word corresponding to the letter string based on the second candidate word list.
As a further improvement of the foregoing technical solution, the calculating a word frequency of a word in the first candidate word list to generate a second candidate word list, and determining a target word corresponding to the letter string based on the second candidate word list includes:
when a user selects the target word and inputs the target word, sequentially inputting the first letter of each syllable in the target word, and acquiring a character group consisting of the syllable first letters arranged in sequence in the target word;
acquiring a character group consisting of syllable initial letters input by a user, and comparing a first syllable initial letter of the character group with all letter string combination ranking first letters of a preset syllable index set;
if the first syllable initial obtained from the character group is different from the first letter in the combination ranking of all the letter strings of the preset syllable index set, searching the retrieved character group from the database;
and if the word which is the same as the character group cannot be called from the database, the target word is recorded to obtain a third candidate word list.
As a further improvement of the above technical solution, if a word identical to the character group cannot be called from the database, the entering the target word to obtain a third candidate word list includes:
judging syllables arranged in sequence in the target word according to the third candidate word list;
acquiring all syllable initial letters in the target word so as to enable a new syllable initial letter string combination consisting of all syllable initial letters of the target word to be recorded into the database;
and calculating the previous input use frequency of the target word and recording the previous input use frequency as word frequency, and finishing the recording of the target word input by the user at this time.
As a further improvement of the above technical solution, the calculating a previous practical frequency of the target word and recording the previous practical frequency as a word frequency to complete the recording of the target word input by the user this time includes:
acquiring an alternative index corresponding to the character set from the database, wherein the initial combination of the initial of the syllables of each candidate word in sequence in the alternative index is the same as the character set, and locating a first candidate word in the alternative index from the database;
when a second candidate word positioned after the first candidate word exists in the alternative index, determining that the first candidate word is not the last word, and positioning a second candidate word of the alternative index from the database;
when there is no second candidate word following the first candidate word in the alternative index, determining that the first candidate word is the last word to determine the associated input word of the target word.
As a further improvement of the above technical solution, the acquiring all syllable initial letters in the target word to enable a new syllable initial letter string combination composed of each syllable initial letter of the target word to be entered into the database includes:
training all syllable initials by adopting a hidden Markov model to obtain a new syllable letter string;
and when the new syllable initial string is judged to accord with a preset word spelling rule, combining the new syllable initial string to obtain a new syllable initial string combination and inputting the new syllable initial string combination into the database.
As a further improvement of the above technical solution, when it is found that the segmentation result at least has one syllable combination corresponding to the database, traversing all words stored in the database according to the syllable combination includes:
and searching the first word to the last word from the database, searching the first word to the last word in the word frequency index in the database, and adding the word with the highest word frequency in the word frequency index into the alternative word library to obtain the syllable combination.
As a further improvement of the above technical solution, the obtaining an input letter string and splitting the letter string to obtain at least one split result includes:
acquiring a plurality of English articles, and recording each word in the English articles and the word frequency corresponding to the word;
inputting according to the word sequence in the English article, selecting a plurality of common words in the word bank of the database and recording the common words;
and creating a letter matrix based on the number of the common words to obtain the letter string.
In a second aspect, an embodiment of the present application provides an english word input device, including:
the system comprises an acquisition module, a judgment module and a display module, wherein the acquisition module is used for acquiring an input letter string and segmenting the letter string to obtain at least one segmentation result, and the letter string comprises at least three letters;
the query module is used for traversing all words stored in the database according to the syllable combination when at least one syllable combination corresponding to the database exists in the segmentation result;
the judging module is used for adding the words into a first candidate word list when judging that the words meet the syllable combination, and the first candidate word list is stored in the database;
and the calculation module is used for calculating the word frequency of the words in the first candidate word list to generate a second candidate word list, and determining the target words corresponding to the letter strings based on the second candidate word list.
In a third aspect, an embodiment of the present application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the above-mentioned english word input method when executing the computer program
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored, where the computer program is executed by a processor to implement the above-mentioned english word input method.
Compared with the prior art, the embodiment of the application has the advantages that:
the method comprises the steps of obtaining input letter strings, segmenting the letter strings to obtain one or more segmentation results, inquiring syllable combinations corresponding to the segmentation results in a database, searching all words through the database, comparing all the words with the syllable combinations, adding the searched words meeting the syllable combinations into a first candidate word list, calculating the word frequency of all the words in the first candidate word list, sequencing the words in the first candidate word list to obtain a second candidate word list, determining a target word according to the second candidate word list, performing associative input when the target word is selected and input, re-recording the word frequency of the input target word and the word frequency of the associated input word, positioning the target word input to select a word, namely a phrase, associated with the target word, is convenient and rapid, and can greatly reduce the letter amount of a user, and increases the speed at which the user enters words. In the query stage, the query speed is greatly improved through two-stage indexing, and the waiting time of the user is also shortened. The memory function can also be adopted, the words with higher use frequency are displayed according to the input frequency of the words used by the user, the intelligent induction degree is improved, the difficulty of inputting English words by the user is reduced, and therefore the purpose of quickly and accurately inputting the required English words is achieved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flowchart of an english word input method according to a first embodiment of the present application;
FIG. 2 is a flowchart illustrating an English word input method according to a second embodiment of the present application;
fig. 3 is a flowchart illustrating an english word input method according to a third embodiment of the present application;
FIG. 4 is a flowchart illustrating an English word input method according to a fourth embodiment of the present application;
FIG. 5 is a schematic structural diagram of an English word input device provided in an embodiment of the present application;
fig. 6 is a schematic structural diagram of a terminal device according to an embodiment of the present application.
Description of the main element symbols:
300-English word input means; 310-an acquisition module; 320-a query module; 330-a judgment module; 340-a calculation module; 400-a terminal device; 410-a memory; 420-a processor; 430-computer program.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to" determining "or" in response to detecting ". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.
Referring to fig. 1, fig. 1 is a flow chart illustrating a word input method according to a first embodiment of the present application, where the word input method includes the following steps:
s1: acquiring an input letter string, and segmenting the letter string to obtain at least one segmentation result, wherein the letter string comprises at least three letters;
in this embodiment, a user may directly input an english word through a device such as a virtual keyboard with a keyboard and a touch screen, but when english word input software is not downloaded, the user needs to completely know the composition of the word to correctly input the english word, and usually the user only remembers three letters or partial pronunciation, initials, and the like of the word, and when three letter strings such as abd are input, the letter strings may be segmented into three segmentation results, ab-d, a-bd, and a-b-d.
Further, acquiring a plurality of English articles, and recording each word in the English articles and the word frequency corresponding to the word;
inputting according to the word sequence in the English article, selecting a plurality of common words in the word bank of the database and recording the common words;
and creating a letter matrix based on the number of the common words to obtain the letter string.
It should be noted that, a plurality of english articles may be input into the input method system in advance, or the words appearing in the plurality of english articles may be marked one by querying and inputting english documents, so that each word may be counted and located, and the english words are sequentially combined by 26 letters according to the preset spelling rule. The method comprises the steps of recording the sequence of each word in an input English article, counting the frequency of each word appearing in the input word, recording the frequency as word frequency, selecting a plurality of words in a word bank, generally about 5000, wherein the word bank belongs to a database, and creating a 5000 x 5000 letter matrix, so that each letter in a letter string can be conveniently positioned subsequently, the letter string input by a user can be quickly searched in the word bank for matching, and the result of matching with the input letter string can be quickly displayed when the user inputs English words.
S2: when the segmentation result is inquired to have at least one syllable combination corresponding to the database, traversing all words stored in the database according to the syllable combination;
in this embodiment, the first word to the last word are searched from the database, the first word to the last word in the word frequency index in the database are searched, and the word with the highest word frequency in the word frequency index is added into the candidate word library to obtain the syllable combination. Taking user input abd as an example, three segmentation results of a-b-d, a-bd and ab-d are obtained, at least one syllable combination matched with the segmentation results is searched in a database, the database is traversed according to the syllable combination, namely, all corresponding words such as about, above, abandon and the like are searched, and the segmentation results of corresponding syllable combinations which are not searched in the database can also be screened out, if a-b-d does not accord with preset word spelling rules, so that the matching rate is improved, and the matching accuracy of the searched words and the letter strings input by the user is improved.
It should be noted that, the first word to the last word are searched from the database, the first word to the last word in the word frequency index in the database are searched, and the word with the highest word frequency in the word frequency index is added into the alternative word library to obtain the syllable combination. When searching for English words in the database, the first English word to the last English word are searched out from the word bank of the database, and then the first English word to the last English word are searched out from the word frequency index of the word bank, so that the English words meeting the conditions can be accurately screened out, the English words which the user wants to input can be preferentially used, and the efficiency of searching for the commonly used English words by the user is improved.
S3: when the word is judged to meet the syllable combination, the word is added into a first candidate word list, and the first candidate word list is stored in the database;
in the embodiment, all words are searched in the database and matched with the syllable combination, the words meeting the matching condition are added into the first candidate word list, and the first candidate word list is used for screening the words meeting the syllable combination, which is equivalent to preliminary screening, so that the efficiency of inputting English words by a user is improved.
S4: and calculating the word frequency of the words in the first candidate word list to generate a second candidate word list, and determining a target word corresponding to the letter string based on the second candidate word list.
In this embodiment, in the first candidate word list, the word frequency is calculated for each word in the database, where the word frequency refers to the number of times that the word is used in the same article, the same word bank, and the like, and a second candidate word list can be obtained by sorting according to the word frequency from high to low, and generally 10 numbers are used for sorting, and 10 words can be displayed in the second candidate word list at a time, so that a user can select a complete word to be input by inputting numbers on a keyboard, which is convenient and fast.
Further, referring to fig. 2, fig. 2 is a schematic flow chart of an english word input method according to a second embodiment of the present application, where S4 further includes S41 to S44, and the method specifically includes the following steps:
s41: when a user selects the target word and inputs the target word, sequentially inputting the first letter of each syllable in the target word, and acquiring a character group consisting of the syllable first letters arranged in sequence in the target word;
s42: acquiring a character group consisting of syllable initial letters input by a user, and comparing a first syllable initial letter of the character group with all letter string combination ranking first letters of a preset syllable index set;
s43: if the first syllable initial obtained from the character group is different from the first letter in the combination ranking of all the letter strings of the preset syllable index set, searching the retrieved character group from the database;
s44: and if the word which is the same as the character group cannot be called from the database, the target word is recorded to obtain a third candidate word list.
In this embodiment, all syllables of the target word input by the user are obtained, the first letter of each syllable in the target word input by the user is sequentially input, for example, the gate is input by the user, the character group gt formed by the syllable first letters arranged in sequence in the target word input by the user is obtained, or the character group formed by combining the syllable first letters input by the user is directly obtained, the first syllable first letter g of the character group is compared with the first letter arranged in the combination of all letter strings in the preset syllable index, if the first syllable first letter obtained from the character group is different from the first letter arranged in the combination of all letter strings in the preset syllable index, the positioning fails, and the target word or the character group input by the user is stopped being queried. In addition, if the first syllable initial obtained from the character group is the same as the first letter in the first letter string combination of the preset syllable index, the positioning is successful, whether the second syllable initial positioned after the first syllable initial is judged in the character group, and if the second syllable initial positioned after the first syllable initial is not positioned in the character group, the first syllable initial is determined as the last letter. If the character group has a second syllable letter located after the first syllable letter, a secondary syllable first letter index which is combined with the syllable first letter string started by the same first syllable letter as a set is constructed, the second syllable first letter is located from the secondary syllable first letter, the second syllable letter of the character group is compared with all the letter string combinations of the secondary syllable letter index set which are arranged in the second letter, if the second syllable first letter obtained from the character group is different from all the letter string combinations of the secondary syllable letter index which are arranged in the second letter, the location is failed, and the query of the target word or the letter group input by the user is stopped. If the character set has a third syllable initial which is located after the second syllable initial, a third syllable initial index is constructed which combines the syllable initial starting with the combination of the first syllable initial and the second syllable initial in the above-mentioned order as a set, the third syllable initial is located from the third syllable initial index, and the third syllable initial of the character set is compared with all the letter string combinations of the set of the third syllable initial index in the third letter order. The method can record words input by a user or selected from a candidate word list, can mark and position each letter in a target word, and then performs associative input or association by combining with a preset syllable index, and adds the words input by associative or phrases combined with the words into a third candidate word list, so that the user can input phrases or common words and the like after inputting the target word, can associate each word with the preset syllable index more accurately, and can store the words in order in a database.
Further, referring to fig. 3, fig. 3 is a schematic flow chart of an english word input method according to a third embodiment of the present application, where S44 further includes the following steps S441 to S443, including the following steps:
s441: judging syllables arranged in sequence in the target word according to the third candidate word list;
s442: acquiring all syllable initial letters in the target word so as to enable a new syllable initial letter string combination consisting of all syllable initial letters of the target word to be recorded into the database;
in this embodiment, a hidden markov model is used to train all the syllable initials to obtain a new syllable alphabetic string, and when the new syllable initial string is determined to meet a preset word spelling rule, the new syllable initial string is combined to obtain a new syllable initial string combination and is recorded into the database.
S443: and calculating the previous input use frequency of the target word and recording the previous input use frequency as word frequency, and finishing the recording of the target word input by the user at this time.
In the present embodiment, the third candidate word list stores words
Further, referring to fig. 4, fig. 4 shows a process diagram of an english word input method according to a fourth embodiment of the present application, and S443 further includes S10 to S30, which specifically includes the following steps:
s10: acquiring an alternative index corresponding to the character set from the database, wherein the initial combination of the initial of the syllables of each candidate word in sequence in the alternative index is the same as the character set, and locating a first candidate word in the alternative index from the database;
s20: when a second candidate word positioned after the first candidate word exists in the alternative index, determining that the first candidate word is not the last word, and positioning a second candidate word of the alternative index from the database;
s30: when there is no second candidate word following the first candidate word in the alternative index, determining that the first candidate word is the last word to determine the associated input word of the target word.
In this embodiment, all words in the candidate index are searched one by one from the database and each word is acquired one by one, and so on until the last word listed in the candidate index is confirmed to be searched and acquired, all candidate words in the candidate index are arranged in sequence according to the use frequency of each searched candidate word, all candidate words are displayed and displayed, when a single word in the candidate index is selected and input once by the user, the candidate word selected from the candidate index by the user is recalculated and recorded, the past input use frequency of the user input target word or character group, namely, the candidate word always selected from the candidate index by the user, the past input use frequency of the user input target word or character group, and the past input use frequency of the user input target word and the candidate word selected from the candidate index by the user are recalculated and recorded, the user input target word and the candidate word selected from the candidate index by the user are recalculated and recorded, The character groups all have relevance, and the search of the input word or the character group of the user at this time is completed. In the preset syllable index, the letter string combinations are classified according to the same or similar degree from beginning to end, and all the letter string combinations in all the classifications are arranged according to the number of total letters in sequence.
In addition, when the user inputs the letter sequence, the computer generates a preset syllable index, namely a primary index, according to the letter sequence input by the user, and then generates a secondary word index from the preset syllable index, the word index, namely the secondary index, is provided for the user, so that the user can conveniently select words in the word index. When the computer fails to search out a candidate word identical to the user input word in the word index, the user input word is regarded as a word, the user input word is searched in the word database, the use frequency of the new word is recorded in the word database, and the use frequency of the word input by the user is updated. When the computer fails to search out a candidate word identical to the word input by the user in the word database, the word input by the user is taken as a new word and the new word is added to the user dictionary (word database, word index).
Referring to fig. 5, fig. 5 shows an english word input device 300 provided by the present application, which includes:
an obtaining module 310, configured to obtain an input letter string, and perform segmentation on the letter string to obtain at least one segmentation result, where the letter string includes at least three letters;
a query module 320, configured to traverse all words stored in the database according to the syllable combination when it is queried that at least one syllable combination corresponding to the segmentation result exists in the database;
a determining module 330, configured to add the word to a first candidate word list when it is determined that the word satisfies the syllable combination, where the first candidate word list is stored in the database;
a calculating module 340, configured to calculate word frequencies of words in the first candidate word list to generate a second candidate word list, and determine a target word corresponding to the letter string based on the second candidate word list.
The application provides a method and a device for inputting champion words, which are characterized in that an input letter string is obtained, the letter string is segmented to obtain one or more segmentation results, syllable combinations corresponding to the segmentation results are inquired in a database, all words are searched by traversing the database, all words are compared with the syllable combinations, the searched words meeting the syllable combinations are added into a first candidate word list, word frequencies of all words in the first candidate word list are calculated, the words in the first candidate word list are sequenced to obtain a second candidate word list, a target word is determined according to the second candidate word list, associative input can be carried out when the target word is selected and input, the word frequency of the input target word and the word frequency of the associatively input word are re-recorded, and the target word input can be positioned to select the word, namely a phrase, which is associated with the target word, the method is convenient and quick, can greatly reduce the letter quantity of the user, and improves the speed of inputting words by the user. In the query stage, the query speed is greatly improved through two-stage indexing, and the waiting time of the user is also shortened. The memory function can also be adopted, the words with higher use frequency are displayed according to the input frequency of the words used by the user, the intelligent induction degree is improved, and the aim of quickly and accurately inputting the required English words is fulfilled.
Referring to fig. 6, fig. 6 is a schematic structural diagram of a terminal device according to an embodiment of the present application, as shown in fig. 6, a terminal device 400 includes a memory 410, at least one processor 420, and a computer program 430 stored in the memory 410 and executable on the processor 420, and when the processor 420 executes the computer program 430, the above-mentioned english word input method is implemented.
The terminal device 400 may be a desktop computer, a mobile phone, a tablet computer, a wearable device, an in-vehicle device, an Augmented Reality (AR)/Virtual Reality (VR) device, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, a Personal Digital Assistant (PDA), and other terminal devices, and the specific type of the terminal device is not limited in this embodiment of the present application.
The terminal device 400 may include, but is not limited to, a processor 420, a memory 410. Those skilled in the art will appreciate that fig. 6 is merely an example of the terminal device 400, and does not constitute a limitation of the terminal device 400, and may include more or less components than those shown, or combine some components, or different components, such as may also include input/output devices, etc.
The Processor 420 may be a Central Processing Unit (CPU), and the Processor 420 may be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 410 may in some embodiments be an internal storage unit of the terminal device 400, such as a hard disk or a memory of the terminal device 400. The memory 410 may also be an external storage device of the terminal device 400 in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, provided on the terminal device 400. Further, the memory 410 may also include both an internal storage unit of the terminal device 400 and an external storage device. The memory 410 is used for storing an operating system, an application program, a Boot Loader (Boot Loader), data, and other programs, such as program codes of the computer programs. The memory 410 may also be used to temporarily store data that has been output or is to be output.
It should be noted that, because the content of information interaction, execution process, and the like between the above expression package generation devices/units is based on the same concept as that of the method embodiment of the present application, specific functions and technical effects thereof may be specifically referred to a part of the method embodiment, and details are not described here.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. For the specific working processes of the units and modules in the auxiliary shooting device, reference may be made to the corresponding processes in the foregoing method embodiments, which are not described herein again.
The embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements the steps in the above-mentioned method embodiments.
The embodiments of the present application provide a computer program product, which when running on a mobile terminal, enables the mobile terminal to implement the steps in the above method embodiments when executed.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium and can implement the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing apparatus/terminal apparatus, a recording medium, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signal, telecommunication signal, and software distribution medium. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc. In certain jurisdictions, computer-readable media may not be an electrical carrier signal or a telecommunications signal in accordance with legislative and patent practice.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather "one or more but not all embodiments" unless specifically stated otherwise. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless expressly specified otherwise.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other ways. For example, the above-described apparatus/network device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. An English word input method, comprising:
acquiring an input letter string, and segmenting the letter string to obtain at least one segmentation result, wherein the letter string comprises at least three letters;
when the segmentation result is inquired to have at least one syllable combination corresponding to the database, traversing all words stored in the database according to the syllable combination;
when the word is judged to meet the syllable combination, the word is added into a first candidate word list, and the first candidate word list is stored in the database;
and calculating the word frequency of the words in the first candidate word list to generate a second candidate word list, and determining a target word corresponding to the letter string based on the second candidate word list.
2. The english word input method according to claim 1, wherein said calculating the word frequency of the words in the first candidate word list to generate a second candidate word list, and determining the target word corresponding to the letter string based on the second candidate word list comprises:
when a user selects the target word and inputs the target word, sequentially inputting the first letter of each syllable in the target word, and acquiring a character group consisting of the syllable first letters arranged in sequence in the target word;
acquiring a character group consisting of syllable initial letters input by a user, and comparing a first syllable initial letter of the character group with all letter string combination ranking first letters of a preset syllable index set;
if the first syllable initial obtained from the character group is different from the first letter in the combination ranking of all the letter strings of the preset syllable index set, searching the retrieved character group from the database;
and if the word which is the same as the character group cannot be called from the database, the target word is recorded to obtain a third candidate word list.
3. The method of claim 2, wherein if the same word as the character set cannot be retrieved from the database, entering the target word to obtain a third candidate word list comprises:
judging syllables arranged in sequence in the target word according to the third candidate word list;
acquiring all syllable initial letters in the target word so as to enable a new syllable initial letter string combination consisting of all syllable initial letters of the target word to be recorded into the database;
and calculating the previous input use frequency of the target word and recording the previous input use frequency as word frequency, and finishing the recording of the target word input by the user at this time.
4. The method of claim 3, wherein said calculating the frequency of previous input of said target word is recorded as word frequency, and said recording of said target word input by said user comprises:
acquiring an alternative index corresponding to the character set from the database, wherein the initial combination of the initial of the syllables of each candidate word in sequence in the alternative index is the same as the character set, and locating a first candidate word in the alternative index from the database;
when a second candidate word positioned after the first candidate word exists in the alternative index, determining that the first candidate word is not the last word, and positioning a second candidate word of the alternative index from the database;
when there is no second candidate word following the first candidate word in the alternative index, determining that the first candidate word is the last word to determine the associated input word of the target word.
5. The english word input method according to claim 1, wherein said obtaining all the syllable initials in the target word so that a new syllable initial string combination composed of the respective syllable initials of the target word is entered into the database comprises:
training all syllable initials by adopting a hidden Markov model to obtain a new syllable letter string;
and when the new syllable initial string is judged to accord with a preset word spelling rule, combining the new syllable initial string to obtain a new syllable initial string combination and inputting the new syllable initial string combination into the database.
6. The method as claimed in claim 1, wherein when the query of the segmentation result indicates that at least one syllable combination corresponding to the database exists, traversing all the words stored in the database according to the syllable combination comprises:
and searching the first word to the last word from the database, searching the first word to the last word in the word frequency index in the database, and adding the word with the highest word frequency in the word frequency index into the alternative word library to obtain the syllable combination.
7. The method for inputting english words according to claim 1, wherein the step of obtaining the input letter string and segmenting the letter string into at least one segmentation result comprises:
acquiring a plurality of English articles, and recording each word in the English articles and the word frequency corresponding to the word;
inputting according to the word sequence in the English article, selecting a plurality of common words in the word bank of the database and recording the common words;
and creating a letter matrix based on the number of the common words to obtain the letter string.
8. An English word input device, comprising:
the system comprises an acquisition module, a judgment module and a display module, wherein the acquisition module is used for acquiring an input letter string and segmenting the letter string to obtain at least one segmentation result, and the letter string comprises at least three letters;
the query module is used for traversing all words stored in the database according to the syllable combination when at least one syllable combination corresponding to the database exists in the segmentation result;
the judging module is used for adding the words into a first candidate word list when judging that the words meet the syllable combination, and the first candidate word list is stored in the database;
and the calculation module is used for calculating the word frequency of the words in the first candidate word list to generate a second candidate word list, and determining the target words corresponding to the letter strings based on the second candidate word list.
9. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 7.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08272780A (en) * | 1995-01-30 | 1996-10-18 | Mitsubishi Electric Corp | Processor and method for chinese input processing, and processor and method for language processing |
| US20080077396A1 (en) * | 2006-09-27 | 2008-03-27 | Wen-Lian Hsu | Typing Candidate Generating Method for Enhancing Typing Efficiency |
| CN101556508A (en) * | 2009-05-08 | 2009-10-14 | 腾讯科技（深圳）有限公司 | Candidate phrase generating method, equipment, system and device in input method |
| CN102012748A (en) * | 2010-11-30 | 2011-04-13 | 哈尔滨工业大学 | Statement-level Chinese and English mixed input method |
| CN103207682A (en) * | 2011-12-19 | 2013-07-17 | 国家电网公司 | Syllable segmentation-based Uighur, Kazakh and Kirghiz intelligent input method |
| CN103886043A (en) * | 2014-03-11 | 2014-06-25 | 北京搜狗科技发展有限公司 | Method and device for showing candidate items |
| CN110555091A (en) * | 2019-08-29 | 2019-12-10 | 韶关市启之信息技术有限公司 | Associated word generation method and device based on word vectors |
-
2021
- 2021-01-21 CN CN202110079610.5A patent/CN112748811A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08272780A (en) * | 1995-01-30 | 1996-10-18 | Mitsubishi Electric Corp | Processor and method for chinese input processing, and processor and method for language processing |
| US20080077396A1 (en) * | 2006-09-27 | 2008-03-27 | Wen-Lian Hsu | Typing Candidate Generating Method for Enhancing Typing Efficiency |
| CN101556508A (en) * | 2009-05-08 | 2009-10-14 | 腾讯科技（深圳）有限公司 | Candidate phrase generating method, equipment, system and device in input method |
| CN102012748A (en) * | 2010-11-30 | 2011-04-13 | 哈尔滨工业大学 | Statement-level Chinese and English mixed input method |
| CN103207682A (en) * | 2011-12-19 | 2013-07-17 | 国家电网公司 | Syllable segmentation-based Uighur, Kazakh and Kirghiz intelligent input method |
| CN103886043A (en) * | 2014-03-11 | 2014-06-25 | 北京搜狗科技发展有限公司 | Method and device for showing candidate items |
| CN110555091A (en) * | 2019-08-29 | 2019-12-10 | 韶关市启之信息技术有限公司 | Associated word generation method and device based on word vectors |
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