CN104898855A - System and method for inputting texts on basis of devices with rockers - Google Patents
System and method for inputting texts on basis of devices with rockers Download PDFInfo
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Abstract
The invention discloses a system and a method for inputting texts on the basis of devices with rockers. The system comprises the input device, a handwriting feature extracting module, a handwriting SVG (scalable vector graphics) module, a handwriting model training module, a word bank association algorithm module, an interface information control module and the display device. The input device is connected with the handwriting feature extracting module and can transmit a series of plane coordinates of handwriting inputted by a user, the handwriting feature extracting module and the handwriting model training module are connected with the handwriting SVG module and can respectively input handwriting feature information and result feedback information, the handwriting SVG module is connected with the word bank association algorithm module and the interface information control module and can output handwriting identification results, the word bank association algorithm module is connected with the interface information control module and can output screened most possible words in association modes, and the interface information control module is connected with the display device and can output animation information. The system and the method have the advantages that the feedback information can be transmitted into the handwriting model training module by the user according to whether input results are correct or not, and is used for training novel handwriting SVG models, accordingly, the identification accuracy can be continuously improved, and the input efficiency can be obviously improved by the aid of the system and the method.
Description
Technical field
What the present invention relates to is a kind of technology of field of computer peripherals, specifically a kind of text input system based on band rocking bar equipment and method.
Background technology
Be sitting in when sofa using Xbox or intelligent television, the letter inputting several similar user name or movie title is conveniently very common thing.Demand game host and intelligent television using rocking bar carry out text event detection exists always, and increases fast along with greatly enriching of internet content.The new technologies such as speech recognition still can not replace traditional inputting interface, as keyboard and rocking bar under many circumstances as a kind of optional text event detection scheme.The text event detection demand such as registration, search, note, Email increased on intelligent television or game host, effective text event detection means will improve an experience for these functions greatly, also lay a good foundation for note and further developing of Email.
Rocking bar kind equipment is widely used in intelligent television, game and vehicle entertainment system as a kind of instantiate live Controls, it comprises rocking bar or its variant form, include but not limited to game paddle rocking bar, handheld device rocking bar, vehicle-mounted Comprehensive Control knob, annular multi-direction button.
The method that use rocking bar main at present carries out text event detection is that cursor selects virtual keyboard input method.The method shows one piece of dummy keyboard on screen, uses rocking bar to move cursor and select the letter on keyboard to input, wherein:, alphabetic keyboard and Qwerty keyboard are most popular keyboard arrangement modes.This character input method is widely used in game machine (PSP as Sony slaps machine and PS main frame, the Xbox main frame etc. of Microsoft), intelligent television, vehicle-mounted information and entertainment system (as BMW iDrive, benz COMAND, Audi MMI etc.).The advantage of this input mode is that study threshold is low, and shortcoming is that efficiency is lower, and input process is dry as dust, and the notice keeping dummy keyboard owing to needing user, this input method can not realize blind input.
There is researcher to propose abroad and be similar to hand-written new input way, such as Graffiti, Unistrokes and EdgeWrite.Rocking bar is difficult to accurately " to write " the complex plane track of letter due to its physical property, and therefore these input methods have carried out simplifying writing to facilitate to letter.Graffiti and Unistrokes is that the use pointer proposed the nineties in 20th century carries out hand-written input method.They, by letter being simplified to a stroke, are easy to write, and improve the effect of machine recognition.The physical edge that EdgeWrite adds a square frame assists rocking bar to write.The font of each letter contains angle on a series of square frame and limit.Compared with selecting inputting method with tradition, these input methods comparatively select inputting method to have can the advantage of blind input.But user needs to learn new alphabet, therefore input speed is at the beginning slow.Game Controller Text entry with Alphabetic and Multi in CHI meeting in 2007 ?Tap Selection Keyboard article propose the input method using two rocking bars on Xbox360 handle to control two keyboards respectively to carry out inputting.When this input method uses input through keyboard based on user, right-hand man is responsible for two zoness of different respectively, qwerty keyboard be divide into two pieces and improves input efficiency.But still need the notice that user keeps dummy keyboard, blind input cannot be realized.
Through finding the retrieval of prior art, open (bulletin) the day 2005.04.20 of Chinese patent literature CN1607491, disclose a kind of Chinese version word input system and method, allow user by using operating rod or its coordinator, add the first few stroke that word needs, word is input in the device of such as mobile phone or PDA.Because just mobile operating bar adds the one or more strokes being used for starting written word, even if or sometimes before the arbitrary stroke of interpolation, user also can find a word wanted from the option table of display.This option table be context-sensitive, rely on last time input word and different so that user can have the word wanted of the candidate of maximum possible.But the prior art is compared with the present invention, its insurmountable technical matters comprises that 31 kinds of stroke forms of Chinese character operate with 5 kinds of operating rod morphologically can not be completely corresponding, and novice users needs memory, and study threshold is higher; The tilted direction of operating rod moves and is difficult to control, easy maloperation when moving to 4:30 direction and 7:30 direction in this patent; Lack the mechanism helping user in use to learn; Feedback cannot being seen on software interface during operation, when carrying out a stroke input as used operating rod, the stroke of concrete input can not be seen on software interface.
Open (bulletin) the day 2005.01.19 of Chinese patent literature CN1567160, disclose a kind of input device and How It Works thereof, input device comprises: a direction device, to detect and to export a plurality of direction, export one of those corresponding directions for during input one word according to character stroke handle bar device for steering; One control circuit is coupled to direction device, one of those directions export direction device coding and storage, and compares with database, and exports the plural candidate word in one of those directions corresponding.This How It Works comprises: receive input one direction; By direction encoding and storage; Compare with a database, export a plurality of candidate characters in this direction corresponding.This technology utilizes the direction device input characters of Joystick-type or steering-wheel type, only need utilization orientation information can be depicted according to stroke by word and reach input characters result once finger steering; Input through keyboard need not be used only to use direction device to coordinate Input Software just can reach text event detection and space can be saved; Only with on the other hand accusing direction processed and input characters need not departure direction device, therefore use simply.But the prior art is compared with the present invention, its insurmountable technical matters comprises between character stroke with direction good not corresponding, is difficult to memory; Some direction output unit such as rocking bar is difficult to accurately export 8 directions, particularly tilted direction; Lack picture feedback; Lack the mode helping user learning to use.
Summary of the invention
The present invention is directed to prior art above shortcomings, propose a kind of text input system based on band rocking bar equipment and method, can conveniently realize blind defeated, the learning difficulty that make use of rocking bar is low, makes the present invention to significantly improve input efficiency.
The present invention is achieved by the following technical solutions:
The present invention relates to a kind of text input system based on band rocking bar equipment, comprising: the association of input equipment, handwriting characteristic extraction module, person's handwriting SVG model, handwriting model training module, dictionary algoritic module, interface information control module, display device, wherein:
Input equipment is connected with handwriting characteristic extraction module and transmits a series of planimetric coordinatess of the person's handwriting that user inputs, handwriting characteristic extraction module and handwriting model training module are all connected with person's handwriting SVG model and input person's handwriting characteristic information and input results feedback information respectively, person's handwriting SVG model is associated algoritic module respectively and is connected with interface information control module and exports the result of person's handwriting identification with dictionary, dictionary association algoritic module is connected with interface information control module and under association's pattern, exports the most possible word filtered out, interface information control module is connected with display device and exports animation information, user imports feedback information into handwriting model training module according to input results correctness, for training new person's handwriting SVG model, thus improve constantly the accuracy rate of identification.
Under association's input pattern, person's handwriting SVG model and dictionary are associated algoritic module and are connected and the result transmitting person's handwriting identification, namely possible letter and probability thereof; Under non-association pattern, person's handwriting SVG model is directly connected with interface information control module, and the result transmitting person's handwriting identification is selected for user, and the quantity according to probability size alternative result is no more than 3.
Described person's handwriting SVG model, carries out learning classification by on-line study mechanism to the handwriting trace of user and correct recognition result, to be optimized SVG model, thus improves the accuracy rate of character classification further.
The present invention relates to the text entry method of said system, comprise the following steps: first by adopt the rocking bar touching in rocking bar motion or leave border, rocking bar gets back to center and reverse three kinds of states split track and according to curvature threshold segmentation characteristic vector pickup track characteristic on border, and be trained to the SVG model of the handwriting trace for Real time identification user, adopt SVG model to carry out character classification judgement to the rocking bar input trajectory carrying out feature extraction equally again, and export a series of possible letter and probability thereof.
Described method preferably switches between association's input pattern (whole word input) and non-association input pattern (letter-by-letter input), under association's input pattern, the character classification judged result of all tracks inputted provides the highest word of probability by calculating joint probability with the word in dictionary, and along with continuation input continuous renewal.Under non-association input pattern, probability is higher than threshold value and the character judged result that quantity is no more than three will be supplied to user selects.
Described method, specifically comprises the following steps:
Step 1, gather initial user letter track sample characteristics train SVG learning model, specifically comprise:
The planimetric coordinates of the alphabetical handwriting trace of 1.1 reading;
1.2 according to rocking bar motion in rocking bar touching or leave border, rocking bar gets back to center and whether reverse three kinds of condition adjudgement add new stroke on border, each stroke is made up of a series of coordinate points;
1.3 screen stroke according to sampled point quantity, remove noise;
Each stroke in 1.4 tracks is split the proper vector for being similar to straight-line segment according to certain curvature threshold again;
1.5, from the multinomial feature of each characteristic vector pickup, comprise distance, angle, absolute position, absolute angle, absolute distance and skew;
1.6 according to track characteristic set training SVG model.
Step 2, a rocking bar input trajectory to be identified, specifically comprises:
2.1 gather a rocking bar input trajectory coordinate data;
2.2 extract track characteristic;
2.3 import SVG learning model;
2.4 export recognition result, comprise multiple letter and probability thereof, when present mode is for association's input pattern, enters step 3, otherwise enter step 4;
Step 3, according to track identification result, dictionary to be screened, specifically comprises:
3.1 remove according to this recognition result the word losing possibility in dictionary;
3.2 judge now whether dictionary is empty;
If 3.3 dictionaries are sky provide prompting, if not for empty removal in input field superposes impossible letter in alphabetical group.
In step 4, selection candidate list, letter inputs, and specifically comprises:
4.1 screen recognition result according to probability threshold values, only retain the letter that probability is greater than threshold values;
Letter the highest for probability shows by 4.2 by default, and in addition first three recognition result of probability is alternatively shown;
If there is no target letter in 4.3 acquiescences or candidate list, delete current results and re-enter, otherwise continue next step;
The selected letter of 4.4 users;
The selected letter of 4.5 input field display input;
SVG model is upgraded according to letter and corresponding input trajectory after 4.6 successful input alphabets.
Step 5, selection word or continuation input alphabet, specifically comprise:
5.1 use HMM algorithms to calculate joint probability according to the word frequency of the possible result of letter each in word and probability and word;
Word in dictionary to arrange by probability and alternatively shows by 5.2 from big to small, and upgrades picture default word and word candidates table;
If 5.4 select word from candidate list, then input this word; If do not selected, continue input alphabet track, repeat step 1 ~ 4, until selected word;
5.4 words input successfully and upgrade SVG model according to letter and corresponding input trajectory.
Technique effect
Compared with prior art, invention increases the efficiency using rocking bar kind equipment to carry out English input.On the one hand, the study threshold for novice users is very low, and input efficiency is higher at the very start.On the other hand, on-line study mechanism continuous renewal user writes sample, and when making to use for a long time, system meets user writing custom more, and input speed and accuracy rate significantly promote.
Accompanying drawing explanation
Fig. 1 is the exemplary function structure chart of input method system;
Fig. 2 is the algorithm flow schematic diagram extracting characteristic module;
Fig. 3 is the algorithm flow schematic diagram of training SVG model;
Fig. 4 is the algorithm flow schematic diagram of association's input pattern;
Fig. 5 is the algorithm flow schematic diagram of non-association input pattern;
Fig. 6 is a kind of schematic diagram that may use the rocking bar equipment Xbox360 handle of this input system;
Fig. 7 is a kind of schematic diagram that may use the rocking bar equipment PSP game machine of this input system;
Fig. 8 is a kind of schematic diagram that may use the rocking bar equipment TV/set-top box remote controller of this input system;
Fig. 9 is a kind of schematic diagram that may use the rocking bar equipment vehicle mounted guidance knob of this input system;
Figure 10 uses rocking bar to write letter and uses touch pad to write the schematic diagram of the track of letter;
Figure 11 is the schematic diagram of the English inputting interface of the present invention.
Embodiment
Elaborate to embodiments of the invention below, the present embodiment is implemented under premised on technical solution of the present invention, give detailed embodiment and concrete operating process, but protection scope of the present invention is not limited to following embodiment.
Embodiment 1
As shown in Figure 6, a kind of rocking bar kind equipment Xbox360 handle of this implementation system support.Xbox360 handle has two rocking bars, user can use one of them rocking bar to write, and uses another rocking bar to select.In user test, employ the rocking bar in the upper left corner for writing, the rocking bar in the lower right corner is selected, and actually can set according to user habit.Three buttons X, A, B on handle are set to delete, determine and associate mode switch function respectively.Figure 11 example inputting interface comprises input field and association's candidate bar, and input field is for showing feedback animation and the letter after determining, association's candidate bar for selecting possible word, does not exist in association's pattern in non-association pattern.
The recognition method using rocking bar to carry out writing has used for reference touch pad to a certain extent.But both still have huge difference.As shown in Figure 10, the track on touch pad spreads out in one plane and has obvious breakpoint, and the track using rocking bar to write normally continuous print, a lot of stroke can overlap on border.This is because when using rocking bar to write, moving near physical boundary is the most natural and full blast.In order to split stroke, after track is divided into several stroke, more respectively according to curvature threshold values, cutting is carried out to each stroke part.Therefore each track can be subdivided into multiple stroke, and each stroke is made up of a series of near linear section again.For each near linear section, be all therefrom extracted 7 features, comprise distance, angle, absolute position, absolute angle, absolute distance and skew.Certainly because a letter may have multiple literary style, therefore each letter has the track of multiple correspondence.
Write the feature that extracts sample for being trained to a SVG (Scalable Vector Graphics) model from user, this model will be used for the handwriting trace of Real time identification user.For sample supplier, this system is more accurately at the very start.For other users, find that the accuracy of diversity on system of sample has significant impact.Except allowing sample as far as possible cover more how possible writing style, the on-line study mechanism of proposition can improve the recognition effect of system gradually along with the input of user.Two kinds of input patterns are provided: association's input pattern and non-association input pattern in system.
In association's input pattern, user inputs by word.For each alphabetical track of user writing, SVG model all can provide multiple possible recognition result and corresponding probability.In the letter identified, accuracy rate is excluded lower than the meeting of threshold values, and the letter that remaining accuracy rate is higher is presented on input field cursor place in the mode of superposition after the screening of HMM algorithm.In the input process of a word, user often inputs a letter, the word existed in the recognition result of a series of tracks that HMM algorithm all can input in whole word according to user and dictionary calculates joint probability, probability be 0 word result can be excluded, being reflected on picture is exactly corresponding letter disappearance in alphabetical group that superposes, and all the other possible words are arranged in association's hurdle candidate bar from big to small by probability.Therefore the whole input process of a word is exactly the result just having started at every turn to input is all alphabetical group that is superimposed, and along with input alphabetical one by one, the letter of superposition reduces gradually, and the target word of user is appeared in one's mind out gradually.Target word to appear speed in one's mind relevant with the size of dictionary to the character of word itself.When a word inputs successfully, on-line study mechanism will each letter in learning word and corresponding track, makes SVG model more meet the writing style of user, improves recognition accuracy.
In non-association pattern, user often inputs a track, and 3 letters that in the result identified, probability is the highest can be arranged in input cursor awaits user by probability size order and select, and after user selects certain letter, corresponding letter just completes input.This letter and corresponding track will be brought in SVG model through on-line study mechanism, improve the recognition accuracy for this user.
Claims (6)
1. the text input system based on band rocking bar equipment, it is characterized in that, comprise: input equipment, handwriting characteristic extraction module, person's handwriting SVG model, handwriting model training module, dictionary association algoritic module, interface information control module, display device, wherein: input equipment is connected with handwriting characteristic extraction module and transmits a series of planimetric coordinatess of the person's handwriting that user inputs, handwriting characteristic extraction module and handwriting model training module are all connected with person's handwriting SVG model and input person's handwriting characteristic information and input results feedback information respectively, person's handwriting SVG model is associated algoritic module respectively and is connected with interface information control module and exports the result of person's handwriting identification with dictionary, dictionary association algoritic module is connected with interface information control module and under association's pattern, exports the most possible word filtered out, interface information control module is connected with display device and exports animation information, user imports feedback information into handwriting model training module according to input results correctness, for training new person's handwriting SVG model, thus improve constantly the accuracy rate of identification.
2. system according to claim 1, is characterized in that, under association's input pattern, person's handwriting SVG model and dictionary are associated algoritic module and be connected and the result transmitting person's handwriting identification, namely possible letter and probability thereof; Under non-association pattern, person's handwriting SVG model is directly connected with interface information control module, and the result transmitting person's handwriting identification is selected for user, and the quantity according to probability size alternative result is no more than 3.
3. system according to claim 1, it is characterized in that, described person's handwriting SVG model, by on-line study mechanism, learning classification is carried out to the handwriting trace of user and correct recognition result, to be optimized SVG model, thus improve the accuracy rate of character classification further.
4. the text entry method of a system according to above-mentioned arbitrary claim, it is characterized in that, comprise the following steps: first by adopt the rocking bar touching in rocking bar motion or leave border, rocking bar gets back to center and reverse three kinds of states split track and according to curvature threshold segmentation characteristic vector pickup track characteristic on border, and be trained to the SVG model of the handwriting trace for Real time identification user, adopt SVG model to carry out character classification judgement to the rocking bar input trajectory carrying out feature extraction equally again, and export a series of possible letter and probability thereof.
5. method according to claim 4, it is characterized in that, switch between association's input pattern (whole word input) and non-association input pattern (letter-by-letter input), under association's input pattern, the character classification judged result of all tracks inputted provides the highest word of probability by calculating joint probability with the word in dictionary, and along with continuation input continuous renewal.Under non-association input pattern, probability is higher than threshold value and the character judged result that quantity is no more than three will be supplied to user selects.
6. the method according to claim 4 or 5, is characterized in that, described method, specifically comprises the following steps:
Step 1, gather initial user letter track sample characteristics train SVG learning model, specifically comprise:
The planimetric coordinates of the alphabetical handwriting trace of 1.1 reading;
1.2 according to rocking bar motion in rocking bar touching or leave border, rocking bar gets back to center and whether reverse three kinds of condition adjudgement add new stroke on border, each stroke is made up of a series of coordinate points;
1.3 screen stroke according to sampled point quantity, remove noise;
Each stroke in 1.4 tracks is split the proper vector for being similar to straight-line segment according to certain curvature threshold again;
1.5, from the multinomial feature of each characteristic vector pickup, comprise distance, angle, absolute position, absolute angle, absolute distance and skew;
1.6 according to track characteristic set training SVG model;
Step 2, a rocking bar input trajectory to be identified, specifically comprises:
2.1 gather a rocking bar input trajectory coordinate data;
2.2 extract track characteristic;
2.3 import SVG learning model;
2.4 export recognition result, comprise multiple letter and probability thereof, when present mode is for association's input pattern, enters step 3, otherwise enter step 4;
Step 3, according to track identification result, dictionary to be screened, specifically comprises:
3.1 remove according to this recognition result the word losing possibility in dictionary;
3.2 judge now whether dictionary is empty;
If 3.3 dictionaries are sky provide prompting, if not for empty removal in input field superposes impossible letter in alphabetical group;
In step 4, selection candidate list, letter inputs, and specifically comprises:
4.1 screen recognition result according to probability threshold values, only retain the letter that probability is greater than threshold values;
Letter the highest for probability shows by 4.2 by default, and in addition first three recognition result of probability is alternatively shown;
If there is no target letter in 4.3 acquiescences or candidate list, delete current results and re-enter, otherwise continue next step;
The selected letter of 4.4 users;
The selected letter of 4.5 input field display input;
SVG model is upgraded according to letter and corresponding input trajectory after 4.6 successful input alphabets;
Step 5, selection word or continuation input alphabet, specifically comprise:
5.1 use HMM algorithms to calculate joint probability according to the word frequency of the possible result of letter each in word and probability and word;
Word in dictionary to arrange by probability and alternatively shows by 5.2 from big to small, and upgrades picture default word and word candidates table;
If 5.4 select word from candidate list, then input this word; If do not selected, continue input alphabet track, repeat step 1 ~ 4, until selected word;
5.4 words input successfully and upgrade SVG model according to letter and corresponding input trajectory.
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| CN109126125A (en) * | 2018-07-03 | 2019-01-04 | 西交利物浦大学 | Text entry method based on double rocking lever controller under reality environment |
| CN109758763A (en) * | 2019-01-07 | 2019-05-17 | 网易（杭州）网络有限公司 | Character input method and device based on game pad |
| CN117409422A (en) * | 2023-12-15 | 2024-01-16 | 吉林大学 | Oracle retrieval method based on handwriting input |
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| CN104898855B (en) | 2017-12-19 |
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