CN111078028B - Input method, related device and readable storage medium - Google Patents
Input method, related device and readable storage medium 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
- G06F3/0236—Character input methods using selection techniques to select from displayed items
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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
- G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
- G06F3/0487—Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser
- G06F3/0488—Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
- G06F3/04883—Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures for inputting data by handwriting, e.g. gesture or text
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Abstract
The application discloses an input method, related equipment and a readable storage medium, wherein after a user input track is acquired, weights of candidate words of at least two input modes are determined according to the user input track, final candidate results are determined according to the weights of the candidate words of the at least two input modes and are displayed to a user, the final candidate results simultaneously contain the candidate words of the at least two input modes, based on the scheme, the input mode combining the at least two input modes can be realized, the user can simultaneously use the at least two input modes in one input process, and the input efficiency is improved.
Description
Technical Field
The present application relates to the field of input methods, and more particularly, to an input method, a related device, and a readable storage medium.
Background
With the continuous development of social science and technology, intelligent electronic devices with touch screens are becoming popular, and accordingly, in order to support the user input function of such intelligent electronic devices, various touch screen input modes have been developed, such as: pinyin input mode, stroke input mode, handwriting input mode, slide input mode, and the like.
At present, in terms of two touch screen input modes, namely a handwriting input mode and a sliding input mode, a user can only select to use the handwriting input mode or select to use the sliding input mode in one input process, when the user selects to use the handwriting input mode, the intelligent electronic equipment can only identify a track formed by a position moved by the user on a screen to obtain a handwriting input result, and when the user selects to perform sliding input, the intelligent electronic equipment can only identify a track formed by the position moved by the user on the screen to obtain a sliding input result.
Since the handwriting input method and the slide input method are consistent in terms of user interaction, and input is performed by a trajectory formed by a position where the user moves on the screen, an input method in which the handwriting input method and the slide input method are combined is required in order for the user to input more efficiently.
Disclosure of Invention
The present application has been made in view of the above-mentioned problems, and has as its object to provide an input method, a related apparatus, and a readable storage medium. The specific scheme is as follows:
an input method, comprising:
collecting a user input track;
determining the weight of each input mode candidate word according to the user input track; each input mode is one of at least two input modes;
Determining a final candidate result according to the weight of each input mode candidate word;
and displaying the final candidate result.
Optionally, the determining the weight of each input mode candidate word according to the user input track includes:
calculating the weight of each input mode of the user input track;
acquiring the priority of candidate words of each input mode of the user input track;
and determining the weight of the candidate word of each input mode according to the weight of each input mode and the priority of the candidate word of each input mode.
Optionally, the calculating the weight of each input mode of the user input track includes:
determining at least one characteristic of the user input trajectory;
respectively calculating the weight of each input mode of the at least one feature;
and calculating the weight of each input mode of the user input track according to the weight of each input mode of the at least one feature.
Optionally, the determining at least one characteristic of the user input trajectory includes:
determining the character of a pen starting area of the user input track, and/or the character of a pen starting direction, and/or the character of horizontal and vertical projection length, and/or the character of degree of dispersion.
Optionally, calculating a weight of each input mode of the initial region feature includes:
acquiring coordinates of a first point of the user input track;
judging whether the coordinate of the first point of the user input track is in a preset pen starting area of each input mode;
when the coordinate of the first point of the user input track is in the preset pen starting area of each input mode, determining the weight of each input mode of the pen starting area characteristic as a first numerical value;
and when the coordinate of the first point of the user input track is not in the preset pen starting area of each input mode, determining the weight of each input mode of the pen starting area characteristic as a second numerical value.
Optionally, calculating a weight of each input mode of the starting direction feature includes:
acquiring an angle of a first stroke of the user input track;
acquiring a reference angle of each input mode;
and determining the weight of each input mode of the starting direction characteristic according to the angle of the first stroke of the user input track and the reference angle of each input mode.
Optionally, calculating the weight of each input mode of the horizontal and vertical projection length features includes:
Calculating the total distance of the user input track moving in the horizontal direction;
calculating the total distance of the user input track moving in the vertical direction;
and calculating the weight of each input mode of the horizontal and vertical projection length characteristics according to the total distance of the movement of the user input track in the horizontal direction and the total distance of the movement of the user input track in the vertical direction.
Optionally, calculating a weight of each input mode of the discrete degree feature includes:
calculating variances of points contained in the user input track;
and calculating the weight of each input mode of the discrete degree feature according to the variance of the points contained in the user input track and a preset discrete degree parameter.
Optionally, the determining the final candidate result according to the weight of each input mode candidate word includes:
and sequencing at least two input mode candidate words according to the order of the weights from large to small to generate a final candidate result.
Optionally, the at least two input modes include:
handwriting input mode and slide input mode.
An input device, comprising:
the acquisition unit is used for acquiring a user input track;
The candidate word weight determining unit is used for determining the weight of each input mode candidate word according to the user input track; each input mode is one of at least two input modes;
the candidate result determining unit is used for determining a final candidate result according to the weight of each input mode candidate word;
and the candidate result display unit is used for displaying the final candidate result.
Optionally, the candidate word weight determining unit includes:
the weight calculating unit is used for calculating the weight of each input mode of the user input track;
a priority obtaining unit, configured to obtain a priority of a candidate word of each input mode of the user input track;
and the weight determining unit is used for determining the weight of the candidate word of each input mode according to the weight of each input mode and the priority of the candidate word of each input mode.
Optionally, the weight calculating unit includes:
a feature determination unit for determining at least one feature of the user input trajectory;
the feature weight calculation unit is used for calculating the weight of each input mode of the at least one feature respectively;
And the input mode weight calculation unit is used for calculating the weight of each input mode of the user input track according to the weight of each input mode of the at least one feature.
Optionally, the feature determining unit is specifically configured to:
determining the character of a pen starting area of the user input track, and/or the character of a pen starting direction, and/or the character of horizontal and vertical projection length, and/or the character of degree of dispersion.
Optionally, the feature weight calculation unit includes: a pen-starting region feature weight calculation unit;
the starting area characteristic weight calculation unit is used for acquiring the coordinate of a first point of the user input track; judging whether the coordinate of the first point of the user input track is in a preset pen starting area of each input mode; when the coordinate of the first point of the user input track is in the preset pen starting area of each input mode, determining the weight of each input mode of the pen starting area characteristic as a first numerical value; and when the coordinate of the first point of the user input track is not in the preset pen starting area of each input mode, determining the weight of each input mode of the pen starting area characteristic as a second numerical value.
Optionally, the feature weight calculation unit includes: a pen-starting direction characteristic weight calculation unit;
the starting direction characteristic weight calculation unit is used for obtaining the angle of the first stroke of the user input track; acquiring a reference angle of each input mode; and determining the weight of each input mode of the starting direction characteristic according to the angle of the first stroke of the user input track and the reference angle of each input mode.
Optionally, the feature weight calculation unit includes: the horizontal and vertical projection length characteristic weight calculation unit;
the horizontal and vertical projection length characteristic weight calculation unit is used for calculating the total distance of the user input track moving in the horizontal direction; calculating the total distance of the user input track moving in the vertical direction; and calculating the weight of each input mode of the horizontal and vertical projection length characteristics according to the total distance of the movement of the user input track in the horizontal direction and the total distance of the movement of the user input track in the vertical direction.
Optionally, the feature weight calculation unit includes: a discrete degree feature weight calculation unit;
The discrete degree characteristic weight calculation unit is used for calculating the variance of points contained in the user input track; and calculating the weight of each input mode of the discrete degree feature according to the variance of the points contained in the user input track and a preset discrete degree parameter.
Optionally, the candidate result determining unit is specifically configured to:
and sequencing at least two input mode candidate words according to the order of the weights from large to small to generate a final candidate result.
Optionally, the at least two input modes include:
handwriting input mode and slide input mode.
An input system includes a memory and a processor;
the memory is used for storing programs;
the processor is configured to execute the program to implement the steps of the input method as described above.
A readable storage medium having stored thereon a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the input method as described above.
By means of the technical scheme, the application discloses an input method, related equipment and a readable storage medium, after a user input track is acquired, weights of candidate words of at least two input modes are determined according to the user input track, a final candidate result is determined according to the weights of the candidate words of the at least two input modes and is displayed to a user, the final candidate result simultaneously comprises the candidate words of the at least two input modes, based on the scheme, the input mode combining the at least two input modes can be realized, the user can use the at least two input modes simultaneously in one input process, and input efficiency is improved.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the application. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
FIG. 1 is a schematic flow chart of an input method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a user input track formed by a user moving a handwriting tool on a keyboard of an intelligent electronic device according to an embodiment of the present application;
FIG. 3 is a schematic diagram showing final candidate results according to an embodiment of the present disclosure;
fig. 4 is a schematic diagram of a preset pen-up region in a handwriting input mode according to an embodiment of the application;
FIG. 5 is a schematic diagram of a preset pen-up region of a sliding input mode according to an embodiment of the present application;
fig. 6 is a schematic diagram of a reference angle of a handwriting input mode according to an embodiment of the application;
FIG. 7 is a schematic view of a reference angle of a sliding input mode according to an embodiment of the present application;
FIG. 8 is a schematic diagram of an input device according to an embodiment of the present application;
Fig. 9 is a schematic structural diagram of an input system according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Referring to fig. 1, fig. 1 is a flow chart of an input method disclosed in an embodiment of the application, the method includes the following steps:
s101: user input trajectories are collected.
When a user uses an intelligent electronic device (such as a smart phone, a tablet computer and the like) with a touch screen, if the user has an input requirement, various operations (such as moving a handwriting tool on the touch screen, clicking the touch screen by the handwriting tool) can be performed on the touch screen of the intelligent electronic device through the handwriting tool (such as fingers, handwriting pens and the like) to generate touch events, so that a plurality of points can be formed, and the points can form a user input track, in other words, the user input track is a data set formed by coordinates of the plurality of points. The coordinates of each point contain coordinate values in the x and y directions.
For easy understanding, referring to fig. 2, fig. 2 is a schematic diagram of a user input track formed when a user moves a handwriting tool on a keyboard of an intelligent electronic device according to an embodiment of the present application, where a track corresponding to a "good" word in the keyboard of fig. 2 is a user input track, and as can be seen from fig. 2, the user input track includes a plurality of points.
In the present application, the user input track can be collected in various ways, and the way of collecting the user input track is a mature technology at present, so the present application is not repeated.
S102: determining the weight of each input mode candidate word according to the user input track; each input mode is one of at least two input modes.
As an implementation manner, in the present application, the user input track may be generated by the user on the premise of selecting at least two input modes, and when the user selects at least two input modes, the weight of each input mode candidate word selected by the user needs to be determined according to the user input track. For example, the user selects two input modes, i.e., a handwriting input mode and a slide input mode.
As yet another embodiment, in the present application, the user input track may be generated by the user on the premise of selecting one input mode, and the user input track matches the input mode selected by the user, in which case, at least one other input mode similar to the input mode input principle selected by the user may be determined, the weight of the candidate word of the input mode selected by the user may be determined according to the user input track, and the weight of the candidate word of the input mode similar to the input mode selected by the user may be determined. For example, the input method selected by the user is a handwriting input method, and the other input method similar to the input principle of the input method selected by the user is a slide input method.
As still another embodiment, in the present application, the user input track is generated by the user on the premise of selecting one input mode, but the user input track cannot be matched with the input mode selected by the user, in which case at least two input modes matched with the user input track may be determined, and weights of at least two input mode candidate words matched with the user input track may be determined according to the user input track. For example, the input mode selected by the user is a pinyin input mode, and the input mode matched with the user track is a handwriting input mode and a sliding input mode.
Since the handwriting input mode and the sliding input mode are consistent in user interaction mode, the handwriting input mode and the sliding input mode are input through a relatively obvious track formed by the position of the user moving on the screen, and therefore, in the application, the at least two relatively preferable input modes can be the handwriting input mode and the sliding input mode. However, other input modes (such as pinyin input mode, stroke input mode, etc.) will also move on the screen during the input process, and the position of such movement can be understood as one of the user input tracks, so at least two input modes can also be other input modes besides handwriting input mode and sliding input mode, and the application is not limited in any way.
It should be noted that, the weight of each candidate word in each input manner is determined according to the user input track, that is, the weight of each candidate word in each input manner is determined, and various implementations of determining the weight of each candidate word in each input manner according to the user input track may be implemented, which will be described in detail later herein. The weights of the same candidate word determined may be different in different ways.
S103: and determining a final candidate result according to the weight of the candidate word of each input mode.
In the application, the final candidate result is a candidate word fused with at least two input modes, and the specific fusion modes can be multiple, in the application, the candidate words are fused according to the weight of each input mode candidate word, as an implementation mode, the candidate words of at least two input modes can be sequenced according to the weight of each candidate word from big to small to generate the final candidate result.
It should be noted that, because different manners are adopted, the weights of the same candidate word may be different. Thus, the final candidate results may also be different.
S104: and displaying the final candidate result.
In the application, the final candidate result can be displayed on a candidate bar of the intelligent electronic device keyboard.
For ease of understanding, referring to fig. 3, fig. 3 is a schematic diagram showing a final candidate result according to an embodiment of the present application, where the top column of the keyboard in fig. 3 is the candidate column, and "malicious" and "one" are candidate words. Wherein the weight of the preceding candidate word is greater than the weight of the following candidate word.
In order to distinguish input modes corresponding to different candidate words, the user may identify candidate words of at least one input mode, for example, the input mode corresponding to "write" word "in the upper right corner of" one "in fig. 3, that is, the explanatory candidate word" one ", is a handwriting input mode.
According to the input method disclosed by the embodiment, after the input track of the user is acquired, the candidate words of at least two input modes are determined according to the input track of the user, the final candidate result is determined according to the weights of the candidate words of the at least two input modes and is displayed to the user, the final candidate result simultaneously contains the candidate words of the at least two input modes, based on the method, the input mode combining the at least two input modes can be realized, the user can use the at least two input modes simultaneously in one input process, and the input efficiency is improved.
In the application, the weight of each input mode of the user input track and the priority of each candidate word can be comprehensively considered, and the weight of each candidate word under each input mode can be determined. Therefore, the application also discloses a specific implementation mode for determining the weight of each input mode candidate word according to the input track of the user, and the implementation mode comprises the following steps:
S201: the weight of each input mode of the user input track is calculated.
The weight of each input mode of the user input track refers to a probability value that the user input track matches a certain input mode.
S202: and acquiring the priority of the candidate words of each input mode of the user input track.
The priority of the candidate word of each input mode of the user input track refers to the priority of each candidate word output by the recognition engine of the input mode under a certain input mode. The priority of the candidate word of each input mode of the user input track can be obtained through the recognition engine of each input mode, and the recognition engines of the various input modes can be realized based on the prior art, so that the application is not limited in any way. Taking a handwriting input mode as an example, inputting a user input track to a recognition engine of the handwriting input mode, wherein the recognition engine of the handwriting input mode can output candidate word information, and each candidate word information not only comprises the content of a candidate word but also comprises the priority of the candidate word.
S203: and determining the weight of the candidate word of each input mode according to the weight of each input mode and the priority of the candidate word of each input mode.
In the present application, the weight of each input mode candidate word may be determined in various modes, for example, the weight of each input mode may be calculated, and the sum of the priorities of each input mode candidate word may be calculated, or the product of the weight of each input mode and the priority of each input mode candidate word may be calculated.
For easy understanding, let F be assumed by taking at least two input modes, i.e., handwriting input mode and slide input mode, respectively write (x) For the final weight of the candidate word of the xth handwriting input mode, E write For the weight of handwriting input mode of user input track, f write (x) Priority of the candidate word for the xth handwriting input mode. The final weight of the x-th handwriting input mode candidate word can be calculated by the following formula:
F write (x)＝E write ×f write (x)
suppose F swype (x) For the final weight of the candidate word of the xth sliding input mode, E swype Weights of sliding input modes of user input tracks, f write (x) Priority of the candidate word for the xth slide input mode. The final weight of the x-th slide input mode candidate word can be calculated using the following formula:
F swype (x)＝E swype ＝f swype (x)
the application also discloses an implementation mode for calculating the weight of each input mode of the user input track, which comprises the following steps:
S301: at least one characteristic of the user input trajectory is determined.
The at least one characteristic of the user input trajectory may include any one or more of a pen-up region characteristic, a pen-up direction characteristic, horizontal and vertical projected length characteristics, and a degree of discretization characteristic of the user input trajectory. In this case, it is explained that the probability that the user input trajectory matches with which input method cannot be distinguished from one or more features is higher. Therefore, the more features are considered, the more accurate the weight of each input mode of the resulting user input trajectory.
S302: the weights of each input mode of at least one feature are calculated separately.
In the present application, the weight of each input mode of each feature refers to a probability value that each feature matches a certain input mode. It should be noted that, for different features, the weight of each input mode of the feature may be calculated in different manners, which will be specifically described by the following embodiments, and this embodiment will not be described in detail.
S303: and calculating the weight of each input mode of the user input track according to the weight of each input mode of at least one feature.
In the present application, the weight of each input mode of the user input track may be calculated in various ways, for example, the sum of the weights of each input mode of at least one feature may be calculated as the weight of each input mode of the user input track. Alternatively, the product of the weights for each input mode of the at least one feature may be calculated as the weight for each input mode of the user input trajectory. The present application is not limited in this regard.
For convenience of understanding, at least two input modes are respectively a handwriting input mode and a sliding input mode, and at least one characteristic is exemplified by a pen starting area characteristic, a pen starting direction characteristic, horizontal and vertical projection length characteristics and a discrete degree characteristic of a user input track:
suppose use E write Weight of handwriting input mode representing user input track by E write_r Weight of handwriting input mode representing character of pen-starting area by E write_d Weight of handwriting input mode representing starting direction characteristics by E write_l Hand featuring horizontal and vertical projection lengthWriting the weight of input mode by E write_s Weight of handwriting input mode representing discrete degree characteristics.
The weight of the handwriting input mode of the user input track can be calculated by the following formula:
E write ＝E write_r ×E write_d ×E write_l ×E write_s
Suppose use E swype Weight of slide input mode representing user input track, using E swype_r Weights of sliding input modes indicating the characteristics of the pen-up region, using E swype_d Weights of sliding input modes indicating the character of the starting direction, using E swype_l Weights of sliding input modes for representing horizontal and vertical projection length characteristics are obtained by E swype_s Weights of the slide input method indicating the discrete degree features.
The weight of the slide input mode of the user input trajectory can be calculated by the following formula:
E swype ＝E swype_r ×E swype_d ×E swype_l ×E swype_s
in the application, a specific implementation mode for calculating the weight of each input mode of each feature is also disclosed, and the specific implementation mode is as follows:
as an implementation manner, the application discloses a method for calculating the weight of each input mode of the initial pen region feature, which comprises the following steps:
s401: and acquiring the coordinate of the first point of the user input track.
It should be noted that, the first point of the user input track may be the start point of the user input track, that is, the first point generated when the user operates the touch screen.
S402: judging whether the coordinate of the first point of the user input track is in a preset pen starting area of each input mode; s403 is executed when the coordinates of the first point of the user input track are within the preset pen-up region of each input mode, and S404 is executed when the coordinates of the first point of the user input track are not within the preset pen-up region of each input mode.
The pen-up region is a region for restricting the position of the pen-up point. The pen starting area can be preset in each input mode in the development process.
Taking a handwriting input mode as an example, according to the writing habit of a user, when the user writes characters, the user writes the characters from top to bottom and from left to right. Of course, there are also few letters to start from right to left. In order to be consistent with the writing habit of the user and consider the situation of few characters, when the preset pen starting area of the handwriting input mode is specified, the user is unlikely to start writing from the rightmost side for handwriting input, so that the width of the keyboard can be divided into 5 equal parts in the horizontal direction, the 4/5 area on the left side is the preset pen starting area of the handwriting input mode, and the 1/5 area on the right side is not the preset pen starting area of the handwriting input mode. Similarly, the user is unlikely to start handwriting input from the lowest row of the keyboard upwards, so that the area of the lowest row of keys of the keyboard can be eliminated in the vertical direction, and the rest area is the preset pen starting area of the handwriting input mode.
For easy understanding, referring to fig. 4, fig. 4 is a schematic diagram of a preset pen-starting area of a handwriting input mode according to an embodiment of the present application, and in fig. 4, an area in a frame is the preset pen-starting area of the handwriting input mode.
Taking the sliding input mode as an example, since the input principle of the sliding input mode is that a user clicks a key by sliding on a software disc, if the user performs sliding input according to the principle, the position of starting a pen must be within the area of the input key. Therefore, the preset pen-starting area of the sliding input mode can be an area corresponding to the letter keys in the keyboard.
For ease of understanding, referring to fig. 5, fig. 5 is a schematic diagram of a preset pen-starting area of a sliding input mode according to an embodiment of the present application, and in fig. 5, an area in a frame is the preset pen-starting area of the sliding input mode.
S403: and determining the weight of each input mode of the starting area characteristic as a first numerical value.
S404: and determining the weight of each input mode of the starting area characteristic as a second numerical value.
In the present application, if the pen-starting point is located in a preset pen-starting region of a certain input mode, the weight of the input mode of the pen-starting region feature is determined to be a first value, and if the pen-starting point is located outside the preset pen-starting region of the certain input mode, the weight of the input mode of the pen-starting region feature is determined to be a second value.
For ease of understanding, assume x 0 ，y 0 The abscissa and ordinate, respectively, of the first point of the user input trajectory, if x 0 ，y 0 When the handwriting input mode is in a preset pen starting area, determining a weight E of the handwriting input mode with characteristics of the pen starting area write_r 1, if x 0 ，y 0 When the handwriting input mode is not in the preset pen starting area, determining the weight E of the handwriting input mode with the characteristics of the pen starting area write_r Is 0. Assuming that the preset pen-up region of the handwriting input mode is simply referred to as a handwriting pen-up region, the formula is as follows:
let x be 0 ，y 0 The abscissa and ordinate, respectively, of the first point of the user input trajectory, if x 0 ，y 0 When the preset pen starting area of the sliding input mode is provided, determining the weight E of the sliding input mode of the character of the pen starting area swype_r 1, if x 0 ，y 0 When the sliding input mode is not in the preset pen starting area, determining the weight E of the sliding input mode of the character of the pen starting area swype_r Is 0. Assuming that the preset pen-up region of the sliding input mode is simply referred to as a sliding pen-up region, the formula is as follows:
further, when the preset pen-up regions of at least two input modes overlap, the weights of at least two input modes of the pen-up region feature are both the first values, and when this is the case, it is explained that the probability that the user input track matches with which input mode cannot be distinguished from the pen-up region feature is higher, so that other features of the user input track can be considered.
As still another embodiment, the present application discloses a method for calculating weights of each input mode of a starting direction feature, which may include the following steps:
s501: and acquiring the angle of the first stroke of the user input track.
It should be noted that, the angle of the first stroke of the user input track may be specifically obtained by first extracting the first stroke of the user input track, and then calculating the angle of the first stroke. The extraction mode of the first pen strokes and the calculation mode of the angles of the first pen strokes can be realized by adopting the existing mature algorithm, and the application is not repeated.
S502: and acquiring the reference angle of each input mode.
It should be noted that, the manner of obtaining the reference angle of each input manner may be different according to the input manner.
Taking handwriting input mode as an example, according to statistics of characters, the condition that the first stroke of a single character starts to be horizontal left, inclined left and horizontal upward does not occur. Thus, if the first pen of the user is detected as having these conditions, it may be considered not to be handwriting input. Therefore, a preset angle interval can be set for the handwriting input mode, when the angle of the first stroke is in the interval, the user input track can be considered to be matched with the handwriting input mode, and when the angle interval of the first stroke is not in the interval, the user input track can be considered to be unmatched with the handwriting input mode. Therefore, the reference angle of the handwriting input mode can be a preset angle interval.
It should be noted that, in the present application, the preset angle interval of the handwriting input mode may take a checked value, for example, (0, 255), or may be dynamically adjusted according to the habit of the user.
For easy understanding, referring to fig. 6, fig. 6 is a schematic diagram showing reference angles of a handwriting input mode according to an embodiment of the present application, and in the circular area of fig. 6, the angle corresponding to the gray area is a preset angle interval of the handwriting input mode.
Taking a sliding input mode as an example, according to the rule of the combination of the initial and final of the Chinese pinyin, the second letter of the pinyin can only be a e i o u h v n. If you are input, the Pinyin string is "ni" and the second Pinyin letter is "i". Thus, the possibilities of each letter key to a few keys ae i o u h v n on the keyboard can be exhausted.
For ease of understanding, referring to fig. 7, fig. 7 is a schematic diagram illustrating reference angles of a sliding input mode according to an embodiment of the present application. As can be seen from fig. 7, taking the key D as an example, according to the rule of initial and final combinations, only the possible combination is DA, DE, DU, DI, DO, so if the start point of the first stroke is D, the user wants to make a sliding input, and the end point of the first stroke can only be A, E, U, I, O.
Therefore, in the application, the current key corresponding to the first point of the first stroke can be determined, then the target key corresponding to the current key is determined according to the initial and final combination of the Chinese pinyin, and then the angle of the target key is calculated. The angle of the target key is the reference angle of the sliding input mode.
When the angle of the target key is calculated, a straight line formed by connecting the current key and the central point of the target key can be obtained, and the inclination angle of the straight line is the angle of the target key.
S503: and determining the weight of each input mode of the starting direction characteristic according to the angle of the first stroke of the user input track and the reference angle of each input mode.
In the present application, different modes may be adopted, and the weight of each input mode of the starting direction feature is determined according to the angle of the first stroke of the user input track and the reference angle of each input mode, which will be described in detail below.
As an implementation manner, the present application provides a specific implementation manner of determining the weight of each input mode of the starting direction feature according to the angle of the first stroke of the user input track and the reference angle of each input mode, where the modes may be:
Judging whether the angle of the first stroke of the user input track is within a preset angle interval of each input mode or not; when the angle of the first stroke of the user input track is within the preset angle interval of each input mode, determining the weight of each input mode of the starting direction characteristic as a first numerical value; and when the angle of the first pen stroke of the user input track is not in the preset angle interval of each input mode, determining the weight of each input mode of the starting direction characteristic as a second numerical value.
For ease of understanding, a handwriting input method will be described below as an example.
Suppose E write_d For the weight of the handwriting input mode of the starting direction characteristic, θ is the angle of the first stroke, and the value range is 15 ° to 255 °, the weight of the handwriting input mode of the starting direction characteristic can be calculated according to the following formula:
as another embodiment, the present application provides another specific embodiment of determining the weight of each input mode of the starting direction feature according to the angle of the first stroke of the user input track and the reference angle of each input mode, where the modes may be: and calculating a normal distribution probability value corresponding to the target key according to the angle of the first stroke of the user input track and the angle of the target key, and determining that the weight of the sliding input mode of the starting direction characteristic is the highest value of the normal distribution probability corresponding to the target key.
For ease of understanding, a slide input method will be described as an example.
In the process of starting the pen, a certain error exists between the direction drawn by the user and the direction of the actual key and the key, and the error can be considered to satisfy normal distribution. If the current user-initiated point is on the D-key, the direction of the first pen may only be to the key A, E, U, I, O. If the normal distribution is satisfied in each direction, the probability of the key D sliding over the respective angles is the highest value of the normal distributions of the key directions.
Thus can be assumed to E swype_d Weight of sliding input mode for starting direction characteristic, { R } is target key of current key, x is angle of first pen stroke, θ i Is the angle of the ith target key.
The normal distribution probability formula is as follows:
wherein the parameter μ is θ i Because is in theta i Is the center point. In order to reach a value of 1 for the highest point, the parameter sigma isThe calculation formula of the weight of the sliding input mode capable of obtaining the starting direction characteristic after being brought in is specifically as follows:
as still another embodiment, the present application discloses a method for implementing the weight of each input mode of calculating the horizontal and vertical projection length features, which may include the following steps:
S601: and calculating the total distance of the movement of the user input track in the horizontal direction.
In the present application, the total distance the user input trajectory moves in the horizontal direction may be calculated from the coordinates of the points in the user input trajectory. Let L be s For the total distance of the movement of the user input track in the horizontal direction, n is the number of points in the user input track, and x i Is the x coordinate value, y of the ith point i Is the y-coordinate value of the i-th point. The specific calculation method is as follows:
s602: a total distance the user input trajectory moves in a vertical direction is calculated.
In the present application, the total distance the user input trajectory moves in the vertical direction may be calculated from the coordinates of the points in the user input trajectory. Let L be h For the total distance of the movement of the user input track in the vertical direction, n is the number of points in the user input track, and x i Is the x coordinate value, y of the ith point i Is the y-coordinate value of the i-th point. The specific calculation method is as follows:
s603: and calculating the weight of each input mode of the horizontal and vertical projection length characteristics according to the total distance of the movement of the user input track in the horizontal direction and the total distance of the movement of the user input track in the vertical direction.
In the application, the weight of each input mode of the horizontal and vertical projection length characteristics can be calculated according to the ratio of the total distance of the movement of the user input track in the horizontal direction to the total distance of the movement of the user input track in the vertical direction.
Taking at least two input modes as a handwriting input mode and a sliding input mode as an example, when the input is performed in the sliding input mode, the area formed by the keys of the keyboard is rectangular, and the area is far longer than the vertical direction in the horizontal direction, so that in most cases, the distance of the user input track moving in the horizontal direction is far longer than the distance of the user input track moving in the vertical direction in the input process. And writing is carried out according to the character form when the handwriting input mode is adopted, wherein the moving distance of the user input track in the horizontal direction is equivalent to the moving distance in the vertical direction, or the moving distance in the vertical direction is longer. Therefore, the weight of the handwriting input mode of the horizontal and vertical projection length characteristics and the weight of the sliding input mode of the horizontal and vertical projection length characteristics can be calculated based on the ratio of the total distance of the movement of the user input track in the horizontal direction to the total distance of the movement of the user input track in the vertical direction.
Suppose E write_l Weight of handwriting input mode for horizontal and vertical projection length characteristics, E swype_l For the weight of the sliding input mode of the horizontal and vertical projection length characteristics, the calculation formula can be as follows:
as still another embodiment, the present application discloses a method for implementing the weight of each input mode for calculating the discrete degree feature, which may include the following steps:
s701: and calculating the discrete degree characteristics of the user input track.
In the present application, the variance of points in the user input trajectory may be calculated as a discrete degree feature of the user input trajectory.
Assuming that S is a discrete degree feature, n is the number of points in the track input by the user, xi, yi are coordinate values of the ith point, an average value of x and an average value of y can be calculated:
the degree of discretization is characterized by:
s702: and calculating the weight of each input mode of the discrete degree features according to the discrete degree features of the user input track and preset discrete degree parameters.
In the application, the discrete degree characteristics of the user input track and the absolute value of the difference between the preset discrete degree parameters can be obtained first, and then the weight of each input mode of the discrete degree characteristics is calculated according to the ratio of the absolute value of the difference to the preset discrete degree parameters.
For easy understanding, the present application is described in detail by taking at least two input modes as handwriting input mode and sliding input mode as examples, and the specific steps are as follows:
according to the input principle, the handwriting input mode identifies that the key of the user input track is a track path, and the sliding input mode identifies that the key of the user input track is a turning point in the track and a passing position, and how the curve of the track has no meaning on sliding input. In general, the positions of the points formed by the handwriting input method are more concentrated, and the positions of the points formed by the slide input method are more dispersed.
Suppose E write_s Weight of handwriting input mode as discrete degree feature, E swype_s The weight of the sliding input mode with discrete degree characteristics, a is a preset discrete degree parameter, and can be adjusted through actual conditions, and the calculation formula can be as follows:
the input device disclosed in the embodiments of the present application is described below, and the input device described below and the input method described above may be referred to correspondingly.
Referring to fig. 8, fig. 8 is a schematic structural diagram of an input device according to an embodiment of the present application. As shown in fig. 8, the input device may include:
an acquisition unit 81 for acquiring a user input trajectory;
A candidate word weight determining unit 82, configured to determine a weight of each input mode candidate word according to the user input track; each input mode is one of at least two input modes;
a candidate result determining unit 83, configured to determine a final candidate result according to the weight of each input mode candidate word;
and a candidate result presentation unit 84, configured to present the final candidate result.
As an embodiment, the candidate word weight determining unit includes:
the weight calculating unit is used for calculating the weight of each input mode of the user input track;
a priority obtaining unit, configured to obtain a priority of a candidate word of each input mode of the user input track;
and the weight determining unit is used for determining the weight of the candidate word of each input mode according to the weight of each input mode and the priority of the candidate word of each input mode.
As an embodiment, the weight calculation unit includes:
a feature determination unit for determining at least one feature of the user input trajectory;
the feature weight calculation unit is used for calculating the weight of each input mode of the at least one feature respectively;
And the input mode weight calculation unit is used for calculating the weight of each input mode of the user input track according to the weight of each input mode of the at least one feature.
As an embodiment, the feature determining unit is specifically configured to:
determining the character of a pen starting area of the user input track, and/or the character of a pen starting direction, and/or the character of horizontal and vertical projection length, and/or the character of degree of dispersion.
As an embodiment, the feature weight calculation unit includes: a pen-starting region feature weight calculation unit;
the starting area characteristic weight calculation unit is used for acquiring the coordinate of a first point of the user input track; judging whether the coordinate of the first point of the user input track is in a preset pen starting area of each input mode; when the coordinate of the first point of the user input track is in the preset pen starting area of each input mode, determining the weight of each input mode of the pen starting area characteristic as a first numerical value; and when the coordinate of the first point of the user input track is not in the preset pen starting area of each input mode, determining the weight of each input mode of the pen starting area characteristic as a second numerical value.
As an embodiment, the feature weight calculation unit includes: a pen-starting direction characteristic weight calculation unit;
the starting direction characteristic weight calculation unit is used for obtaining the angle of the first stroke of the user input track; acquiring a reference angle of each input mode; and determining the weight of each input mode of the starting direction characteristic according to the angle of the first stroke of the user input track and the reference angle of each input mode.
As an embodiment, the feature weight calculation unit includes: the horizontal and vertical projection length characteristic weight calculation unit;
the horizontal and vertical projection length characteristic weight calculation unit is used for calculating the total distance of the user input track moving in the horizontal direction; calculating the total distance of the user input track moving in the vertical direction; and calculating the weight of each input mode of the horizontal and vertical projection length characteristics according to the total distance of the movement of the user input track in the horizontal direction and the total distance of the movement of the user input track in the vertical direction.
As an embodiment, the feature weight calculation unit includes: a discrete degree feature weight calculation unit;
The discrete degree characteristic weight calculation unit is used for calculating the variance of points contained in the user input track; and calculating the weight of each input mode of the discrete degree feature according to the variance of the points contained in the user input track and a preset discrete degree parameter.
As an embodiment, the candidate result determining unit is specifically configured to:
and sequencing at least two input mode candidate words according to the order of the weights from large to small to generate a final candidate result.
As an implementation manner, the at least two input modes include:
handwriting input mode and slide input mode.
Fig. 9 shows a block diagram of a hardware structure of an input system, and referring to fig. 9, the hardware structure of the input system may include: at least one processor 1, at least one communication interface 2, at least one memory 3 and at least one communication bus 4;
in the embodiment of the application, the number of the processor 1, the communication interface 2, the memory 3 and the communication bus 4 is at least one, and the processor 1, the communication interface 2 and the memory 3 complete the communication with each other through the communication bus 4;
processor 1 may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement embodiments of the present application, etc.;
The memory 3 may comprise a high-speed RAM memory, and may further comprise a non-volatile memory (non-volatile memory) or the like, such as at least one magnetic disk memory;
wherein the memory stores a program, the processor is operable to invoke the program stored in the memory, the program operable to:
collecting a user input track;
determining the weight of each input mode candidate word according to the user input track; each input mode is one of at least two input modes;
determining a final candidate result according to the weight of each input mode candidate word;
and displaying the final candidate result.
Alternatively, the refinement function and the extension function of the program may be described with reference to the above.
The embodiment of the present application also provides a storage medium storing a program adapted to be executed by a processor, the program being configured to:
collecting a user input track;
determining the weight of each input mode candidate word according to the user input track; each input mode is one of at least two input modes;
determining a final candidate result according to the weight of each input mode candidate word;
and displaying the final candidate result.
Alternatively, the refinement function and the extension function of the program may be described with reference to the above.
Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (12)
1. An input method, comprising:
collecting a user input track;
calculating the weight of each input mode of the user input track;
acquiring the priority of candidate words of each input mode of the user input track;
determining the weight of the candidate word of each input mode according to the weight of each input mode and the priority of the candidate word of each input mode; each input mode is one of at least two input modes;
determining a final candidate result according to the weight of each input mode candidate word;
displaying the final candidate result;
The determining the weight of the candidate word of each input mode according to the weight of each input mode and the priority of the candidate word of each input mode comprises the following steps:
calculating the weight of each input mode, and obtaining the weight of the candidate word of each input mode by summing the priorities of the candidate words of each input mode,
or,
and calculating the weight of each input mode, and obtaining the weight of the candidate word of each input mode by multiplying the priorities of the candidate words of each input mode.
2. The method of claim 1, wherein calculating the weight for each input mode of the user input trajectory comprises:
determining at least one characteristic of the user input trajectory;
respectively calculating the weight of each input mode of the at least one feature;
and calculating the weight of each input mode of the user input track according to the weight of each input mode of the at least one feature.
3. The method of claim 2, wherein the determining at least one characteristic of the user input trajectory comprises:
determining the character of a pen starting area of the user input track, and/or the character of a pen starting direction, and/or the character of horizontal and vertical projection length, and/or the character of degree of dispersion.
4. A method according to claim 3, wherein calculating weights for each input mode of the start area feature comprises:
acquiring coordinates of a first point of the user input track;
judging whether the coordinate of the first point of the user input track is in a preset pen starting area of each input mode;
when the coordinate of the first point of the user input track is in the preset pen starting area of each input mode, determining the weight of each input mode of the pen starting area characteristic as a first numerical value;
and when the coordinate of the first point of the user input track is not in the preset pen starting area of each input mode, determining the weight of each input mode of the pen starting area characteristic as a second numerical value.
5. A method according to claim 3, wherein calculating weights for each input mode of the start direction feature comprises:
acquiring an angle of a first stroke of the user input track;
acquiring a reference angle of each input mode;
and determining the weight of each input mode of the starting direction characteristic according to the angle of the first stroke of the user input track and the reference angle of each input mode.
6. A method according to claim 3, wherein calculating weights for each input mode of the horizontal and vertical projection length features comprises:
calculating the total distance of the user input track moving in the horizontal direction;
calculating the total distance of the user input track moving in the vertical direction;
and calculating the weight of each input mode of the horizontal and vertical projection length characteristics according to the total distance of the movement of the user input track in the horizontal direction and the total distance of the movement of the user input track in the vertical direction.
7. A method according to claim 3, wherein calculating the weight for each input mode of the discrete level feature comprises:
calculating variances of points contained in the user input track;
and calculating the weight of each input mode of the discrete degree feature according to the variance of the points contained in the user input track and a preset discrete degree parameter.
8. The method of claim 1, wherein determining the final candidate result based on the weight of each input means candidate word comprises:
and sequencing at least two input mode candidate words according to the order of the weights from large to small to generate a final candidate result.
9. The method according to any one of claims 1 to 8, wherein the at least two input modes comprise:
handwriting input mode and slide input mode.
10. An input device, comprising:
the acquisition unit is used for acquiring a user input track;
the candidate word weight determining unit is used for determining the weight of each input mode candidate word according to the user input track; each input mode is one of at least two input modes;
the candidate result determining unit is used for determining a final candidate result according to the weight of each input mode candidate word;
a candidate result display unit for displaying the final candidate result;
the candidate word weight determining unit is specifically configured to calculate a weight of each input mode of the user input track; acquiring the priority of candidate words of each input mode of the user input track; determining the weight of the candidate word of each input mode according to the weight of each input mode and the priority of the candidate word of each input mode;
the determining the weight of the candidate word of each input mode according to the weight of each input mode and the priority of the candidate word of each input mode comprises the following steps:
Calculating the weight of each input mode, and obtaining the weight of the candidate word of each input mode by summing the priorities of the candidate words of each input mode,
or,
and calculating the weight of each input mode, and obtaining the weight of the candidate word of each input mode by multiplying the priorities of the candidate words of each input mode.
11. An input system comprising a memory and a processor;
the memory is used for storing programs;
the processor being configured to execute the program to implement the respective steps of the input method according to any one of claims 1 to 9.
12. A readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the input method according to any one of claims 1 to 9.
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