JP2015135546A - Electronic device, method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an electronic device, a method, and a program capable of easily creating a handwritten document.SOLUTION: According to an embodiment, a method comprises: inputting stroke data corresponding to one or more handwritten strokes; and displaying a plurality of stroke sets identified based on the one or more strokes as a handwritten input candidate, the plurality of stroke sets including a first stroke set corresponding to a shape of the one or more strokes and a second stroke set corresponding to a furigana or Japanese reading aid determined by using the shape of the one or more strokes.

Description

  Embodiments described herein relate generally to a technique for inputting a character string by handwriting.

  In recent years, various electronic devices such as tablet computers, notebook personal computers, smartphones, and PDAs have been developed that can input documents by handwriting.

JP 2008-186056 A

  An object of one embodiment of the present invention is to provide an electronic device, a method, and a program capable of easily creating a handwritten document.

  According to the embodiment, the method inputs stroke data corresponding to one or more strokes described by handwriting, and sets a plurality of stroke sets specified based on the one or more strokes as candidates for handwriting input. The plurality of stroke sets includes a first stroke set corresponding to the one or more stroke shapes and a second kana corresponding to the reading kana determined using the one or more stroke shapes. A stroke set.

FIG. 6 is a perspective view illustrating an example of an external appearance of the electronic apparatus according to the embodiment. The block diagram which shows an example of cooperation operation | movement with an electronic device and another apparatus. The figure which shows an example of the handwritten document handwritten by a touchscreen display. The figure which shows an example of the time series information which is a collection of stroke data. 1 is a block diagram illustrating an example of a system configuration of an electronic device. The figure which shows the home screen displayed by an electronic device. The figure which shows the note preview screen displayed by an electronic device. The figure which shows the setting screen displayed by an electronic device. The figure which shows the page edit screen displayed by an electronic device. The figure which shows the search dialog displayed by an electronic device. The block diagram which shows the function structure of the handwritten note application program performed with an electronic device. The figure which shows an example of the data structure of a suggestion feature table. The figure which shows an example of the data structure of a suggestion keyword table. The figure which shows an example of the data structure of a reading kana table. The flowchart which shows an example of a feature-value registration process. The figure for demonstrating concretely an integrated character recognition process. The flowchart which shows an example of a candidate display process. The figure for demonstrating concretely about the priority of each keyword. The figure for demonstrating concretely about the priority of each keyword. The figure which shows an example of the candidate display area where a handwriting input candidate is displayed. The figure which shows an example of the handwriting input area where the handwriting input candidate selected by the user was displayed.

  Hereinafter, embodiments will be described with reference to the drawings.

  FIG. 1 is a perspective view illustrating an example of an external appearance of an electronic apparatus according to an embodiment. This electronic device is, for example, a pen-based portable electronic device that can be handwritten with a pen or a finger. This electronic device can be realized as a tablet computer, a notebook personal computer, a smartphone, a PDA, or the like. Below, the case where this electronic device is implement | achieved as the tablet computer 10 is demonstrated. The tablet computer 10 is a portable electronic device that is also called a tablet or a slate computer, and the main body 11 has a thin box-shaped housing.

  The touch screen display 17 is attached to be superposed on the upper surface of the main body 11. The touch screen display 17 incorporates a flat panel display and a sensor configured to detect a contact position of a pen or a finger on the screen of the flat panel display. The flat panel display may be, for example, a liquid crystal display (LCD). As the sensor, for example, a capacitive touch panel, an electromagnetic induction digitizer, or the like can be used. Hereinafter, a case where both of the two types of sensors, the digitizer and the touch panel, are incorporated in the touch screen display 17 will be described. For this reason, the touch screen display 17 can detect not only a touch operation on the screen using a finger but also a touch operation on the screen using the pen 100.

  The pen 100 may be, for example, a digitizer pen (electromagnetic induction pen). The user can perform a handwriting input operation on the touch screen display 17 using the pen 100 (pen input mode). In the pen input mode, a trajectory of the movement of the pen 100 on the screen, that is, a stroke handwritten by a handwriting input operation is obtained, and thereby a plurality of strokes input by handwriting are displayed on the screen. The locus of movement of the pen 100 while the pen 100 is in contact with the screen corresponds to one stroke. A plurality of strokes constitute characters, symbols, and the like. A set of a large number of strokes corresponding to handwritten characters, handwritten graphics, handwritten tables and the like constitutes a handwritten document.

  In the present embodiment, this handwritten document is stored in the storage medium as time series information (handwritten document data) indicating the coordinate sequence of the trajectory of each stroke and the order relationship between the strokes, not image data. However, this handwritten document may be generated based on the image data. Details of the time-series information will be described later with reference to FIG. 4, but the time-series information indicates the order in which a plurality of strokes are handwritten, and includes a plurality of stroke data respectively corresponding to the plurality of strokes. In other words, the time series information means a set of time series stroke data respectively corresponding to a plurality of strokes. Each stroke data corresponds to a certain stroke, and includes a coordinate data series (time series coordinates) corresponding to each point on the locus of this stroke. The order of arrangement of the stroke data corresponds to the order in which the strokes are handwritten.

  The tablet computer 10 can read existing arbitrary time-series information from the storage medium and display a handwritten document corresponding to the time-series information, that is, a plurality of strokes indicated by the time-series information on the screen. The plurality of strokes indicated by the time series information are also a plurality of strokes input by handwriting.

  Furthermore, the tablet computer 10 according to the present embodiment also has a touch input mode for performing a handwriting input operation with a finger without using the pen 100. When the touch input mode is valid, the user can perform a handwriting input operation on the touch screen display 17 using a finger. In the touch input mode, a trajectory of finger movement on the screen, that is, a stroke handwritten by a handwriting input operation is obtained, and thereby a plurality of strokes input by handwriting are displayed on the screen.

  The tablet computer 10 has an editing function. This editing function is an arbitrary handwritten portion in a displayed handwritten document selected by the range selection tool in response to an editing operation by the user using the “eraser” tool, the range selection tool, and other various tools ( Handwritten characters, handwritten marks, handwritten graphics, handwritten tables, etc.) can be deleted or moved. Also, an arbitrary handwritten part in the handwritten document selected by the range selection tool can be designated as a search key for searching for a handwritten document. In addition, recognition processing such as handwritten character recognition / handwritten figure recognition / handwritten table recognition can be performed on an arbitrary handwritten portion in a handwritten document selected by the range selection tool.

  In the present embodiment, the handwritten document can be managed as one or a plurality of pages. In this case, a group of time-series information that fits on one screen may be recorded as one page by dividing time-series information (handwritten document data) by area units that fit on one screen. Alternatively, the page size may be variable. In this case, since the page size can be expanded to an area larger than the size of one screen, a handwritten document having an area larger than the screen size can be handled as one page. When one entire page cannot be simultaneously displayed on the display, the page may be reduced and displayed, or the display target portion in the page may be moved by vertical and horizontal scrolling.

  FIG. 2 shows an example of the linking operation between the tablet computer 10 and an external device. The tablet computer 10 includes a wireless communication device such as a wireless LAN, and can execute wireless communication with the personal computer 1. Furthermore, the tablet computer 10 can execute communication with the server 2 on the Internet 3 using a wireless communication device. The server 2 may be a server that executes an online storage service and other various cloud computing services.

  The personal computer 1 includes a storage device such as a hard disk drive (HDD). The tablet computer 10 can transmit time series information (handwritten document data) to the personal computer 1 and record it in the HDD of the personal computer 1 (upload). In order to secure secure communication between the tablet computer 10 and the personal computer 1, the personal computer 1 may authenticate the tablet computer 10 at the start of communication. In this case, a dialog prompting the user to input an ID or password may be displayed on the screen of the tablet computer 10, and the ID of the tablet computer 10 is automatically transmitted from the tablet computer 10 to the personal computer 1. May be.

  Thereby, even when the storage capacity of the tablet computer 10 is small, the tablet computer 10 can handle a large amount of time-series information or a large amount of time-series information.

  Furthermore, the tablet computer 10 reads (downloads) any one or more time-series information recorded in the HDD of the personal computer 1 and displays the stroke indicated by the read time-series information on the screen of the display 17 of the tablet computer 10. Can be displayed. In this case, a list of thumbnails obtained by reducing each page of the plurality of pieces of time-series information may be displayed on the screen of the display 17, or one page selected from these thumbnails may be displayed on the screen of the display 17. You may display with normal size.

  Furthermore, the destination to which the tablet computer 10 communicates may be the server 2 on the cloud that provides a storage service or the like, as described above, instead of the personal computer 1. The tablet computer 10 can transmit time series information (handwritten document data) to the server 2 via the Internet and record it in the storage device 2A of the server 2 (upload). Further, the tablet computer 10 reads (downloads) arbitrary time-series information recorded in the storage device 2A of the server 2, and displays the trajectory of each stroke indicated by the time-series information on the screen of the display 17 of the tablet computer 10. Can be displayed.

  As described above, in this embodiment, the storage medium in which the time series information is stored may be any one of the storage device in the tablet computer 10, the storage device in the personal computer 1, and the storage device in the server 2.

  Next, with reference to FIG. 3 and FIG. 4, the relationship between strokes (characters, figures, tables, etc.) handwritten by the user and time-series information will be described. FIG. 3 shows an example of a handwritten document (handwritten character string) handwritten on the touch screen display 17 using the pen 100 or the like.

  In a handwritten document, in many cases, another character or figure is input by handwriting on the character or figure once input by handwriting. In FIG. 3, the handwritten characters “A”, “B”, and “C” are input by handwriting in this order, and then a handwritten arrow is input by handwriting in the immediate vicinity of the handwritten character “A”. ing.

  The handwritten character “A” is expressed by two strokes (“∧” -shaped trajectory, “−”-shaped trajectory) handwritten using the pen 100 or the like, that is, by two trajectories. The trajectory of the first “∧” -shaped pen 100 handwritten is sampled in real time, for example, at equal time intervals, thereby obtaining the time-series coordinates SD11, SD12,. Similarly, the trajectory of the “−” shaped pen 100 to be handwritten next is also sampled in real time at equal time intervals, thereby obtaining the time series coordinates SD21, SD22,..., SD2n of the “−” shaped stroke.

  The handwritten character “B” is represented by two strokes handwritten using the pen 100 or the like, that is, two trajectories. The handwritten character “C” is represented by one stroke handwritten using the pen 100 or the like, that is, one locus. The handwritten “arrow” is expressed by two strokes handwritten using the pen 100 or the like, that is, two trajectories.

  FIG. 4 shows time-series information 200 corresponding to the handwritten document of FIG. The time series information includes a plurality of stroke data SD1, SD2,. In the time series information 200, these stroke data SD1, SD2,..., SD7 are arranged in time series in the order in which these strokes are handwritten.

  In the time series information 200, the first two stroke data SD1 and SD2 indicate two strokes of the handwritten character “A”, respectively. The third and fourth stroke data SD3 and SD4 indicate two strokes constituting the handwritten character “B”, respectively. The fifth stroke data SD5 indicates one stroke constituting the handwritten character “C”. The sixth and seventh stroke data SD6 and SD7 indicate two strokes constituting the handwritten “arrow”, respectively.

  Each stroke data includes a coordinate data series (time series coordinates) corresponding to one stroke, that is, a plurality of coordinates corresponding to each of a plurality of sampling points on one stroke locus. In each stroke data, the coordinates of a plurality of sampling points are arranged in chronological order in the order in which the strokes are written (sampled order). For example, for the handwritten character “A”, the stroke data SD1 includes coordinate data series (time series coordinates) corresponding to each point on the locus of the stroke of the “∧” shape of the handwritten character “A”, that is, n pieces of data. Coordinate data SD11, SD12,..., SD1n are included. The stroke data SD2 includes coordinate data series corresponding to each point on the trajectory of the stroke of the “−” shape of the handwritten character “A”, that is, n coordinate data SD21, SD22,. Note that the number of coordinate data may be different for each stroke data. If the strokes are sampled at equal time intervals, the lengths of the strokes are different, so the number of sampling points is also different.

  Each coordinate data indicates the X coordinate and Y coordinate of a certain point in the corresponding locus. For example, the coordinate data SD11 indicates the X coordinate (X11) and the Y coordinate (Y11) of the start point of the “∧” -shaped stroke. SD1n indicates the X coordinate (X1n) and Y coordinate (Y1n) of the end point of the “∧” -shaped stroke.

  Each coordinate data may include time stamp information T corresponding to the time point (sampling timing) when the point corresponding to the coordinates is handwritten. The handwritten time may be either absolute time (for example, year / month / day / hour / minute / second) or relative time based on a certain time. For example, absolute time (for example, year / month / day / hour / minute / second) at which the stroke is started is added to each stroke data as time stamp information, and each coordinate data in the stroke data indicates a difference from the absolute time. The relative time may be added as time stamp information T.

  As described above, by using the time series information in which the time stamp information T is added to each coordinate data, the temporal relationship between the strokes can be expressed more accurately. Although not shown in FIG. 4, information (Z) indicating writing pressure may be added to each coordinate data.

  The time series information 200 having the structure as described in FIG. 4 can represent not only the handwriting of each stroke but also the temporal relationship between the strokes. Therefore, by using this time-series information 200, as shown in FIG. 3, the tip of the handwritten “arrow” is written over the handwritten character “A” or close to the handwritten character “A”. However, the handwritten character “A” and the tip of the handwritten “arrow” can be handled as different characters or figures.

  Further, in the present embodiment, as described above, handwritten document data is not stored as an image or character recognition result, but is stored as time-series information 200 composed of a set of time-series stroke data. It can handle handwritten characters without depending on. Therefore, the structure of the time-series information 200 in this embodiment can be commonly used in various countries around the world with different languages.

  FIG. 5 is a diagram showing a system configuration of the tablet computer 10.

  The tablet computer 10 includes a CPU 101, a system controller 102, a main memory 103, a graphics controller 104, a BIOS-ROM 105, a nonvolatile memory 106, a wireless communication device 107, an embedded controller (EC) 108, and the like.

  The CPU 101 is a processor that controls the operation of various modules in the tablet computer 10. The CPU 101 executes various software loaded into the main memory 103 from the nonvolatile memory 106 that is a storage device. These software include an operating system (OS) 201 and various application programs. The various application programs include a handwritten note application program 202. Hereinafter, the handwritten document data is also referred to as a handwritten note. The handwritten note application program 202 has a function for creating and displaying the above handwritten document data, a function for editing the handwritten document data, handwritten document data including a desired handwritten part, and a desired handwritten part in a certain handwritten document data. It has a handwritten document search function for searching.

  The CPU 101 also executes a basic input / output system (BIOS) stored in the BIOS-ROM 105. The BIOS is a program for hardware control.

  The system controller 102 is a device that connects between the local bus of the CPU 101 and various component modules. The system controller 102 also includes a memory controller that controls access to the main memory 103. The system controller 102 also has a function of executing communication with the graphics controller 104 via a PCI EXPRESS serial bus or the like.

  The graphics controller 104 is a display controller that controls the LCD 17 </ b> A used as a display monitor of the tablet computer 10. A display signal generated by the graphics controller 104 is sent to the LCD 17A. The LCD 17A displays a screen image based on the display signal. The LCD 17A, the touch panel 17B, and the digitizer 17C are overlaid on each other. The touch panel 17B is a capacitance-type pointing device for inputting on the screen of the LCD 17A. The touch position on the screen where the finger is touched, the movement of the touch position, and the like are detected by the touch panel 17B. The digitizer 17C is an electromagnetic induction type pointing device for inputting on the screen of the LCD 17A. The contact position on the screen where the pen (digitizer pen) 100 is touched, the movement of the contact position, and the like are detected by the digitizer 17C.

  The wireless communication device 107 is a device configured to execute wireless communication such as wireless LAN or 3G mobile communication. The EC 108 is a one-chip microcomputer including an embedded controller for power management. The EC 108 has a function of turning on or off the tablet computer 10 in accordance with the operation of the power button by the user.

  Next, examples of some typical screens presented to the user by the handwritten note application program 202 will be described.

  FIG. 6 shows an example of the home screen of the handwritten note application program 202. The home screen is a basic screen for handling a plurality of handwritten document data, and can manage notes and set the entire application.

  The home screen includes a desktop screen area 70 and a drawer screen area 71. The desktop screen area 70 is a temporary area for displaying a plurality of note icons 801 to 805 corresponding to a plurality of handwritten notes being worked. Each of the note icons 801 to 805 displays a thumbnail of a page in the corresponding handwritten note. The desktop screen area 70 further displays a pen icon 771, a calendar icon 772, a scrap note (gallery) icon 773, and a tag (label) icon 774.

  The pen icon 771 is a graphical user interface (GUI) for switching the display screen from the home screen to the page editing screen. The calendar icon 772 is an icon indicating the current date. The scrap note icon 773 is a GUI for browsing data (scrap data or gallery data) imported from another application program or from an external file. The tag icon 774 is a GUI for attaching a label (tag) to an arbitrary page in an arbitrary handwritten note.

  The drawer screen area 71 is a display area for browsing a storage area for storing all created handwritten notes. The drawer screen area 71 displays note icons 80A, 80B and 80C corresponding to some handwritten notes in all handwritten notes. Each of the note icons 80A, 80B, and 80C displays a thumbnail of a page in the corresponding handwritten note. The handwriting note application program 202 can detect a certain gesture (for example, a swipe gesture) on the drawer screen area 71 performed by the user using the pen 100 or a finger. In response to detection of this gesture (for example, a swipe gesture), the handwritten note application program 202 scrolls the screen image on the drawer screen area 71 leftward or rightward. Thereby, the note icon corresponding to each arbitrary handwritten note can be displayed in the drawer screen area 71.

  The handwritten note application program 202 can detect another gesture (for example, a tap gesture) on the note icon in the drawer screen area 71 performed by the user using the pen 100 or a finger. In response to detection of a gesture on a note icon on the drawer screen area 71 (for example, a tap gesture), the handwritten note application program 202 moves the note icon to the center of the desktop screen area 70. Then, the handwritten note application program 202 selects a handwritten note corresponding to the note icon, and displays a note preview screen shown in FIG. 7 instead of the desktop screen. The note preview screen shown in FIG. 7 is a screen on which an arbitrary page in the selected handwritten note can be viewed.

  Further, the handwritten note application program 202 can also detect a gesture (for example, a tap gesture) on the desktop screen area 70 performed by the user using the pen 100 or a finger. In response to detecting a gesture (for example, a tap gesture) on a note icon located at the center of the desktop screen area 70, the handwriting note application program 202 selects a handwritten note corresponding to the note icon located at the center. Then, a note preview screen shown in FIG. 7 is displayed instead of the desktop screen.

  Further, the home screen can display a menu. This menu includes a note list button 81A, a note creation button 81B, a note deletion button 81C, a search button 81D, and a setting button 81E displayed in the lower part of the screen, for example, the drawer screen area 71. The note list button 81A is a button for displaying a list of handwritten notes. The note creation button 81B is a button for creating (adding) a new handwritten note. The note deletion button 81C is a button for deleting a handwritten note. The search button 81D is a button for opening a search screen (search dialog). The setting button 81E is a button for opening an application setting screen.

  Although not shown, a return button, a home button, and a recent application button are also displayed below the drawer screen area 71.

  FIG. 8 shows an example of a setting screen that is opened when the setting button 81E is tapped with the pen 100 or a finger.

  This setting screen displays various setting items. These setting items include “backup and restoration”, “input mode (pen or touch input mode)”, “license information”, “help”, and the like.

  When note creation button 81B is tapped with pen 100 or a finger on the home screen, a note creation screen is displayed. Here, the name of the note is input by handwriting in the title field. Note that a notebook cover and paper can be selected. When the creation button is pressed, a new note is created, and the created note is placed in the drawer screen area 71.

  FIG. 7 shows an example of the above-described note preview screen.

  The note preview screen is a screen capable of browsing an arbitrary page in the selected handwritten note. Here, a case where a handwritten note corresponding to the note icon 801 in the desktop screen area 70 of the home screen is selected will be described. In this case, the handwritten note application program 202 can visually recognize a plurality of pages 901, 902, 903, 904 and 905 included in the handwritten note, at least a part of each of these pages 901, 902, 903, 904 and 905, In addition, these pages 901, 902, 903, 904, and 905 are displayed in an overlapping form.

  The note preview screen further displays the pen icon 711, the calendar icon 772, and the scrap note icon 773 described above.

  The note preview screen can further display a menu at the bottom of the screen. This menu includes a home button 82A, a page list button 82B, a page add button 82C, a page edit button 82D, a page delete button 82E, a label button 82F, a search button 82G, and a property display button 82H. The home button 82A is a button for closing the preview of the note and displaying the home screen. The page list button 82B is a button for displaying a list of pages in the currently selected handwritten note. The page addition button 82C is a button for creating (adding) a new page. The edit button 82D is a button for displaying a page edit screen. The page deletion button 82E is a button for deleting a page. The label button 82F is a button for displaying a list of types of labels that can be used. The search button 82G is a button for displaying a search screen. The property display button 82H is a button for displaying the property of this note.

  The handwritten note application program 202 can detect various gestures on the note preview screen performed by the user. For example, in response to detection of a certain gesture, the handwritten note application program 202 changes the page to be displayed at the top to an arbitrary page (page advance, page return). Also, in response to detection of a certain gesture (for example, tap gesture) performed on the top page, or in response to detection of a gesture (for example, tap gesture) performed on the pen icon 771 or editing. In response to detecting a gesture (eg, tap gesture) made on button 82D, handwriting note application program 202 selects the top page and instead of the note preview screen, the page shown in FIG. Display the edit screen.

  The page editing screen in FIG. 9 is a screen that allows a new creation of a page (handwritten page) in a handwritten note, and browsing and editing of an existing page. When the page 901 on the note preview screen in FIG. 7 is selected, the page edit screen displays the contents of the page 901 as shown in FIG.

  In this page editing screen, a rectangular area 500 surrounded by a broken line is a handwritten input area that can be handwritten. In the handwriting input area 500, an input event from the digitizer 17C is used for displaying (drawing) a handwritten stroke, and is not used as an event indicating a gesture such as a tap. On the other hand, in an area other than the handwriting input area 500 on the page editing screen, the input event from the digitizer 17C can also be used as an event indicating a gesture such as a tap.

  The input event from the touch panel 17B is not used for displaying (drawing) a handwritten stroke, but is used as an event indicating a gesture such as a tap and swipe.

  The page editing screen further displays a quick select menu including three types of pens 501 to 503 registered in advance by the user, a range selection pen 504, and an eraser pen 505 at the top of the screen outside the handwriting input area 500. Here, a case where the black pen 501, red pen 502, and marker 503 are registered in advance by the user is described. The user can switch the type of pen to be used by tapping a pen (button) in the quick select menu with the pen 100 or a finger. For example, when a handwriting input operation using the pen 100 is performed on the page editing screen in a state where the black pen 501 is selected by the user using the pen 100 or a tap gesture using a finger, the handwriting note application program 202 is A black stroke (trajectory) is displayed on the page edit screen in accordance with 100 movements.

  The above-mentioned three types of pens in the quick select menu can be switched by operating a side button (not shown) of the pen 100. For each of the above-described three types of pens in the quick select menu, combinations of frequently used pen colors and pen thicknesses can be set.

  The page editing screen further displays a menu button 511, a page return (return to note preview screen) button 512, and a new page addition button 513 at the bottom of the screen outside the handwriting input area 500. The menu button 511 is a button for displaying a menu.

  This menu includes, for example, putting this page in the trash, pasting a part of the copied or cut page, opening the search screen, displaying the export submenu, displaying the import submenu, converting the page to text Buttons for sending an e-mail and displaying a pen case may be displayed. The export submenu is, for example, a function for recognizing a handwritten page displayed on the page editing screen and converting it to an electronic document file, presentation file, image file, etc. Have users select the features to share. For example, the import submenu allows the user to select a function for importing a memo from the memo gallery or a function for importing an image from the gallery. The pen case is a button for calling up the pen setting screen that allows you to change the color (color of the line to be drawn) and thickness (thickness of the line to be drawn) of each of the three types of pens in the quick select menu. is there.

  FIG. 10 shows an example of a search screen (search dialog). FIG. 10 illustrates a case where the search button 82G is selected on the note preview screen shown in FIG. 7 and the search screen (search dialog) is opened on the note preview screen.

  The search screen displays a search key input area 530, a handwriting search button 531, a text search button 532, a delete button 533, and a search execution button 534. The handwriting search button 531 is a button for selecting handwriting search. The text search button 532 is a button for selecting text search. The text search button 532 is a button for selecting text search. The search execution button 534 is a button for requesting execution of search processing.

  In handwriting search, the search key input area 530 is used as an input area for handwriting a character string to be used as a search key, for example. In addition, the user can handwrite not only the handwritten character string but also a handwritten figure, a handwritten table, and the like with the pen 100 in the search key input area 530. For example, when the search execution button 434 is selected by the user in a state where a handwritten character string is input as a search key in the search key input area 530, a stroke set (query stroke set) constituting the handwritten character string is used. A handwriting search for searching for a handwritten document (note) including a stroke set corresponding to the query stroke set is executed. In handwriting search, a stroke set similar to the query stroke set is searched by matching between strokes. In calculating the similarity between the query stroke set and another stroke set, DP (Dynamic Programming) matching may be used.

  In text search, for example, a software keyboard is displayed on the screen. The user can input an arbitrary text (character string) to the search key input area 530 as a search key by operating the software keyboard. When the search execution button 534 is selected by the user in a state where text is input as a search key in the search key input area 530, text search for searching for a handwritten note including a stroke set representing the text (query text) is performed. Executed.

  The handwriting search / text search can be executed for all handwritten documents, or can be executed only for selected handwritten documents. When handwriting search / text search is executed, a search result screen is displayed. On the search result screen, a list of handwritten documents (pages) including a stroke set corresponding to the query stroke set (or query text) is displayed. Note that hit words (a stroke set corresponding to a query stroke set or a query text) are highlighted.

  Next, the functional configuration of the handwritten note application program 202 will be described with reference to FIG.

  The handwritten note application program 202 is a WYSIWYG application capable of handling handwritten document data. The handwritten note application program 202 includes, for example, a display processing unit 301, a time-series information generation unit 302, an editing processing unit 303, a page storage processing unit 304, a page acquisition processing unit 305, a feature amount registration processing unit 306, a work memory 401, and the like. Is provided. The display processing unit 301 includes a handwritten data input unit 301A, a handwriting drawing unit 301B, and a candidate display processing unit 301C.

  The touch panel 17B described above is configured to detect occurrence of events such as “touch (contact)”, “movement (slide)”, and “release”. “Touch (contact)” is an event indicating that an object (finger) on the screen has touched. “Move (slide)” is an event indicating that the contact position has been moved while the object (finger) is in contact with the screen. “Release” is an event indicating that an object (finger) has been released from the screen.

  The digitizer 17C described above is also configured to detect the occurrence of events such as “touch (contact)”, “movement (slide)”, and “release”. “Touch (contact)” is an event indicating that the object (pen 100) has touched the screen. “Move (slide)” is an event indicating that the contact position has been moved while the object (pen 100) is in contact with the screen. “Release” is an event indicating that the object (pen 100) has been released from the screen.

  The handwritten note application program 202 displays a page editing screen for creating, browsing, and editing handwritten page data on the touch screen display 17.

  The display processing unit 301 and the time-series information generation unit 302 receive a “touch (contact)”, “move (slide)”, or “release” event generated by the digitizer 17C, thereby detecting a handwriting input operation. . The “touch (contact)” event includes the coordinates of the contact position. The “movement (slide)” event includes the coordinates of the contact position of the movement destination. Therefore, the display processing unit 301 and the time-series information generating unit 302 can receive a coordinate sequence corresponding to the movement locus of the contact position from the digitizer 17C.

  The display processing unit 301 displays a handwritten stroke on the screen according to the movement of the object (pen 100) on the screen detected using the digitizer 17C. The display processing unit 301 displays the trajectory of the pen 100 while the pen 100 is in contact with the screen, that is, the trajectory of each stroke, on the page editing screen.

  The time series information generation unit 302 receives the above-described coordinate sequence output from the digitizer 17C, and includes time series information (coordinate data sequence) having a structure as described in detail in FIG. 4 based on the coordinate sequence. Generate handwritten data. The time series information generation unit 302 temporarily stores the generated handwritten data in the work memory 401.

  The edit processing unit 303 executes a process for editing the handwritten page currently being displayed. That is, the edit processing unit 303 adds a new stroke (new handwritten character, new handwritten mark, etc.) to the currently displayed handwritten page in response to the editing operation and handwriting input operation performed by the user on the touch screen display 17. Edit processing including processing for adding a character, processing for deleting or moving one or more of the displayed strokes, and the like are executed. Further, the edit processing unit 303 updates the time series information in the work memory 401 in order to reflect the result of the edit process in the time series information being displayed.

  The page storage processing unit 304 stores handwritten page data including a plurality of stroke data corresponding to a plurality of handwritten strokes on the handwritten page being created in the storage medium 402. The storage medium 402 may be, for example, a storage device in the tablet computer 10 or a storage device of the server computer 2.

  The page acquisition processing unit 305 acquires arbitrary handwritten page data from the storage medium 402. The acquired handwritten page data is sent to the display processing unit 301. The display processing unit 301 displays a plurality of strokes corresponding to the plurality of stroke data included in the handwritten page data on the screen.

  When the page storage processing unit 304 stores the handwritten document (data) in the storage medium 402, the feature amount registration processing unit 306 performs character recognition processing on the stroke set constituting the handwritten document. All strokes constituting the handwritten document are converted into character strings (words). The feature amount registration processing unit 306 uses the converted character string as a keyword, and each stroke in the stroke set converted into the keyword and the keyword in the handwritten document (that is, character recognition as the keyword by the character recognition process) is performed. A character recognition result for each stroke set obtained by integrating one stroke in time series order and the number of strokes in the stroke set are associated and registered in the suggest feature table.

  The feature amount registration processing unit 306 registers the converted character string (keyword) and the stroke data corresponding to the stroke set converted into the character string in association with each other in the suggestion keyword table.

  Further, the feature amount registration processing unit 306 registers the converted character string (keyword) and the reading kana of the character string in association with each other in the reading kana table.

  It is assumed that the suggest feature table, the suggest keyword table, and the reading kana table are stored in the storage medium 402, for example.

  Next, details of the display processing unit 301 illustrated in FIG. 11 will be described.

  As described above, the touch screen display 17 detects a touch operation on the screen by the touch panel 17B or the digitizer 17C. The handwritten data input unit 301A is a module that inputs a detection signal output from the touch panel 17B or the digitizer 17C. The detection signal includes coordinate information (X, Y) of the touch position. By inputting such detection signals in chronological order, the handwritten data input unit 301A inputs stroke data corresponding to a stroke described by handwriting. The stroke data (detection signal) input by the handwritten data input unit 301A is supplied to the handwriting drawing unit 301B.

  The handwriting drawing unit 301 </ b> B is a module that draws a handwriting input locus (handwriting) and displays it on the LCD 17 </ b> A of the touch screen display 17. The handwriting drawing unit 301B draws a line segment corresponding to the locus (handwriting) of handwriting input based on the stroke data (detection signal) from the handwriting data input unit 301A.

  When the stroke data input by the handwritten data input unit 301A corresponds to a stroke written by handwriting on the above-described page editing screen (upper handwriting input area 500), the stroke data is displayed as a candidate display processing unit 301C. Also supplied. When stroke data is input by the handwritten data input unit 301A in this way, the candidate display processing unit 301C receives one or more strokes written by handwriting (that is, stroke data supplied from the handwritten data input unit 301A). A plurality of stroke sets specified on the basis of stroke data input at the time point) is displayed in the candidate display area on the page editing screen as candidates for handwriting input by the user. The plurality of stroke sets displayed as candidates for the handwriting input represent, for example, a handwritten character string, and are described with a stroke set (first stroke set) corresponding to one or more stroke shapes described by handwriting and the handwriting. In addition, a stroke set (second stroke set) corresponding to a reading pseudonym determined using one or more stroke shapes is included. Note that the stroke set displayed as a candidate for handwriting input is specified with reference to a suggest feature table, a suggest keyword table, and a reading kana table stored in the storage medium 402 as described later.

  In the following description, a stroke set displayed as a candidate for handwriting input in the candidate display area on the page editing screen is simply referred to as a handwriting input candidate. Among the handwriting input candidates, a stroke set corresponding to one or more stroke shapes is a handwriting input candidate by handwriting, and a stroke set corresponding to a reading kana determined by using the one or more stroke shapes is handwritten by reading a kana. This is called an input candidate. A specific example of the candidate display area where the handwriting input candidates are displayed will be described later.

  When handwriting input candidates (handwriting input candidates by handwriting and handwriting input candidates by reading kana) are displayed in the candidate display area of the page editing screen in this way, the user displays the handwriting input candidates in the handwriting input area 500 (description) ) Can be selected (designated) as a character string or the like. When the user selects a handwriting input candidate displayed in the candidate display area, the handwriting drawing unit 301B displays the handwriting input candidate in the handwriting input area 500 on the page editing screen. At this time, the handwriting drawing unit 301 </ b> B displays the handwriting input candidate in the handwriting input area 500 based on the coordinates of the handwriting input candidate (stroke set) displayed in the candidate display area as described above. Note that the coordinates of the stroke set are relatively determined with reference to time-series coordinates (that is, strokes already written in the handwriting input area 500) included in the already input stroke data.

  Although not shown in FIG. 11, the handwritten note application program 202 includes a search processing unit and the like for executing the above-described handwriting search and text search in addition to the above.

  FIG. 12 shows an example of the data structure of the suggestion feature table stored in the storage medium 402 described above. As shown in FIG. 12, in the suggestion feature table, keywords, character recognition results, and the number of strokes are held (registered) in association with each other. The keyword is a character string (text) corresponding to the above-described handwriting input candidate. The character recognition result indicates the character recognition result for a part of the stroke set of the stroke set that is recognized as a keyword associated with the character recognition result. The number of strokes indicates the number of strokes (that is, the number of strokes) in the stroke set from which the character recognition result associated with the number of strokes is obtained.

  In the example illustrated in FIG. 12, for example, the keyword “air conditioner”, the character recognition result “−”, and the number of strokes “1” are stored in association in the suggestion feature table. According to this, when a stroke set that is recognized as the keyword “air conditioner” is handwritten by the user, the character recognition result when character recognition processing is performed when one stroke is handwritten is “−”. It has been shown.

  In the suggestion feature table, for example, the keyword “air conditioner”, the character recognition result “T”, and the number of strokes “2” are stored in association with each other. According to this, when the stroke set recognized as the keyword “air conditioner” is handwritten by the user, the character recognition result when the character recognition process is performed when two strokes are handwritten is “T”. It has been shown.

  In this way, the suggestion feature table holds, for example, a character recognition result every time 1 is added to the number of strokes (that is, the number of strokes) constituting the keyword “air conditioner”. That is, in the suggestion feature table, as described above, the character recognition result for each stroke set obtained by integrating the strokes in the stroke set recognized as a keyword one by one in time-series order and the number of strokes in the stroke set Stored in association with keywords.

  Although details will be described later, as described above, when handwritten input candidates are displayed, a search is performed using the character recognition result and the number of strokes (that is, the number of strokes) as keys.

  Although the keyword “air conditioner” has been described here, the character recognition result and the number of strokes are similarly stored in association with other keywords (for example, “factory”) in the suggestion feature table.

  FIG. 13 shows an example of the data structure of the suggest keyword table stored in the storage medium 402 described above. As shown in FIG. 13, in the suggestion keyword table, keywords and stroke data as primary keys are stored (registered) in association with each other. The keyword is a character string (text) corresponding to the above-described handwriting input candidate. The stroke data is data (binary data of the stroke) corresponding to a stroke set that is recognized as a keyword associated with the stroke data.

  In the example shown in FIG. 13, for example, the keyword “air conditioner” and stroke data “(10, 10)-(13, 8)-. This indicates that the stroke data corresponding to the stroke set recognized as the keyword “air conditioner” is “(10, 10)-(13, 8)-...”. As described above, the stroke data includes a plurality of coordinates corresponding to a plurality of sampling points on the stroke trajectory.

  Although the keyword “air conditioner” has been described here, the suggestion keyword table similarly stores stroke data in association with other keywords (for example, “factory”, “achievement”, “long throw”, etc.). Yes.

  FIG. 14 shows an example of the data structure of a reading table stored in the storage medium 402 described above. As shown in FIG. 14, in the reading kana table, keywords and reading kana are stored (registered) in association with each other. The keyword is a character string (text) corresponding to the above-described handwriting input candidate. The reading kana indicates the reading kana of the keyword associated with the reading kana.

  In the example illustrated in FIG. 14, for example, the keyword “air conditioner” and the reading kana “air conditioner” are stored in association with each other in the reading kana table. According to this, it is shown that the reading pseudonym of the keyword “air conditioner” is “air conditioner”.

  Similarly, for example, the keyword “factory” and the reading kana “Kojijo” are stored in the reading kana table in association with each other. This indicates that the reading pseudonym of the keyword “factory” is “Koujo”.

  Although the keywords “air conditioner” and “factory” have been described here, the reading kana table similarly stores reading kana corresponding to other keywords (for example, “achievement” and “far-throw”). Yes.

  In the example shown in FIG. 14, the reading kana is described as katakana notation, but the reading kana may be hiragana notation.

  Hereinafter, the operation of the tablet computer 10 according to the present embodiment will be described. Here, among the processes executed by the tablet computer 10 according to the present embodiment, a feature amount registration process and a candidate display process will be described.

  First, the processing procedure of the feature amount registration processing will be described with reference to the flowchart of FIG. The feature amount registration processing is executed by the feature amount registration processing unit 306 when the above-described handwritten document (data) is stored in the storage medium 402.

  In the feature amount registration process, the feature amount registration processing unit 306 acquires the handwritten document from, for example, the work memory 401 when the page storage processing unit 304 stores the handwritten document in the storage medium 402 (block B1). The handwritten document is composed of a stroke set handwritten by the user in the handwriting input area 500 on the page editing screen described above, and includes stroke data corresponding to the stroke set.

  Next, the feature amount registration processing unit 306 performs a character recognition process on the acquired handwritten document (a set of strokes corresponding to the stroke data included therein) (block B2). Thereby, the stroke set which comprises a handwritten document is converted into a character string. At this time, each stroke (corresponding to stroke data) constituting the handwritten document corresponds to a character (character constituting the stroke) to which the stroke belongs in the character string converted by executing the character recognition process. It shall be attached.

  The feature amount registration processing unit 306 performs a morpheme analysis (morpheme analysis) process on the converted character string (block B3). As a result, the converted character string is divided into words. At this time, the feature amount registration processing unit 306 specifies a stroke set belonging to each word divided by the morphological analysis process based on the stroke associated with each character in the character string.

  Next, the feature amount registration processing unit 306 performs integrated character recognition processing on the stroke set belonging to each word divided by the morphological analysis processing (block B4). This integrated character recognition process is a process of acquiring a character recognition result (character string) that is a feature amount for each stroke.

  Here, with reference to FIG. 16, the integrated character recognition processing will be specifically described. Here, for the sake of convenience, a case will be described in which the integrated character recognition process is performed on a stroke set belonging to the word “air conditioner”.

  In this case, the character recognition result when the character recognition process is executed for the stroke (collection) 1001 having the number of strokes (number of strokes) is “−”.

  Next, the character recognition result when the character recognition process is executed for the stroke set 1002 having the number of strokes (number of strokes) is “T”.

  Similarly, the character recognition result when the character recognition process is executed for the stroke set 1003 having the number of strokes (number of strokes) of 3 is “D”.

  Further, the character recognition result when the character recognition process is executed for the stroke set 1004 having the number of strokes (number of strokes) of 4 is “F”.

  The character recognition result when the character recognition process is executed for the stroke set 1005 having the number of strokes (number of strokes) of 5 is “air”.

  When the number of strokes is increased by 1 in this manner, finally, “air conditioner” is obtained as a character recognition result for a stroke set having 9 strokes (number of strokes).

  As described above, when the integrated character recognition process is executed for the stroke set belonging to the word “air conditioner”, the integrated character recognition result 1100 shown in FIG. 16 can be obtained. The integrated character recognition result 1100 includes a word, a character recognition result for a stroke set, and the number of strokes in the stroke set.

  In the above-described block B4, it has been described that the integrated character recognition process is performed on the stroke set belonging to one word. However, the integrated character recognition process includes a plurality of pieces that can be handled as one unit. You may perform with respect to the character string containing a word.

  Returning to FIG. 15 again, the feature amount registration processing unit 306 registers various kinds of information in the above-described suggestion feature table, suggestion keyword table, and reading kana table based on the acquired integrated character recognition result 1100 (block). B5).

  Specifically, the feature amount registration processing unit 306 registers the word (keyword), the character recognition result, and the number of strokes included in the accumulated character recognition result 1100 in association with each other in the suggestion feature table.

  The feature amount registration processing unit 306 registers the word (keyword) included in the integrated character recognition result and the stroke data corresponding to the stroke set belonging to the word in the suggestion keyword table.

  Furthermore, the feature amount registration processing unit 306 registers the word (keyword) included in the integrated character recognition result and the reading kana of the word in the reading kana table in association with each other. The reading kana registered in the reading kana table may be acquired from various dictionaries or the like held in the tablet computer 10 or may be designated (registered) by the user.

  When the same information (for example, keyword) is already held in the suggest feature table, the suggest keyword table, and the reading kana table in the block B5 described above, the information registration process is omitted.

  As described above, according to the feature amount registration process, when a handwritten document is stored in the storage medium 402, necessary information used in a candidate display process, which will be described later, is automatically converted into a suggestion feature table, a suggestion keyword table, and a reading pseudonym. Can be registered in the table.

  Next, a processing procedure of candidate display processing will be described with reference to the flowchart of FIG. The candidate display processing is executed by the candidate display processing unit 301C when stroke data corresponding to a stroke described in handwriting is input in the handwriting input area 500 on the page editing screen described above. The candidate display process is executed each time one stroke is written in the handwriting input area 500 by handwriting.

  In the candidate display process, the candidate display processing unit 301C inputs stroke data corresponding to one stroke described by handwriting by the user in the handwriting input area 500 on the page editing screen (block B11). Hereinafter, the stroke data input in the block B11 is referred to as target stroke data.

  Next, the candidate display processing unit 301C applies a stroke set corresponding to the stroke data input at the time when the target stroke data is input (that is, one or more strokes written in the handwriting input area 500 by handwriting). Character recognition processing is executed for the block (block B12). Specifically, if the target stroke data is stroke data corresponding to the stroke of the nth stroke (n is an integer equal to or greater than 1) of the handwritten character string, for example, the candidate display processing unit 301C has the first stroke to nth. Character recognition processing is executed for the stroke set of the stroke. Thereby, candidate display processing part 301C acquires a character recognition result. In the present embodiment, this character recognition result is used as a feature amount representing the features of the stroke set (shape) of the first stroke to the nth stroke.

  Note that the stroke of the first stroke is specified based on, for example, the positions of other strokes handwritten in the handwriting input area 500.

  The candidate display processing unit 301C searches for a keyword from the suggestion feature table based on the acquired character recognition result and the number of strokes in the stroke set from which the character recognition result is acquired (block B13). In this case, the candidate display processing unit 301C searches the keyword stored in the suggestion feature table in association with the acquired character recognition result and the number of strokes (that is, the number of strokes) in the stroke set from which the character recognition result is acquired. To do. Here, the keyword searched by the candidate display processing unit 301 </ b> C is a keyword corresponding to the handwriting input candidate by handwriting described above.

  Further, the candidate display processing unit 301C searches for a keyword from the reading kana table based on the acquired character recognition result (block B14). In this case, the candidate display processing unit 301C, for example, selects a keyword held in the reading kana table in association with a reading kana including the acquired character recognition result (for example, a reading kana that matches the character recognition result in front). Search for. Here, the keyword searched by the candidate display processing unit 301 </ b> C is a keyword corresponding to the above-described handwritten input candidate based on the reading kana.

  In the above-described reading kana table shown in FIG. 14, it has been described that katakana reading kana is held. However, for example, when a hiragana (reading kana) is written by hand by the user (that is, the first stroke) When the character recognition result for the stroke set of the nth stroke is hiragana), the hiragana is converted into katakana and the search process is executed.

  The candidate display processing unit 301C gives priority to each keyword searched in the blocks B13 and B14 (block B15). The priority of each keyword is given according to the number of strokes in the stroke set from which the character recognition result is acquired. Details of the processing of the block B15 will be described later.

  Next, the candidate display processing unit 301C acquires stroke data corresponding to the stroke set constituting the keyword searched in the blocks B13 and B14 (block B16). Specifically, the candidate display processing unit 301C acquires stroke data held in the suggestion keyword table in association with the searched keyword.

  The candidate display processing unit 301C displays the handwritten input candidate by drawing the acquired stroke data (corresponding stroke set) in the candidate display area on the page editing screen (block B17). This handwriting input candidate is displayed based on the priority given to each keyword in block B15.

  Of the handwritten input candidates displayed by the candidate display processing unit 301C, the stroke set (stroke data stored in the suggest keyword table in association with the keyword) constituting the keyword searched in the block B13 is based on handwriting. A stroke set (stroke data stored in the suggestion keyword table in association with the keyword) displayed as a handwritten input candidate and constituting the keyword searched in block B14 is displayed as a handwritten input candidate based on the reading kana.

  That is, according to the candidate display processing in the present embodiment, the handwriting input candidate (handwriting input candidate by handwriting) based on the shape of one or more strokes handwritten by the user and the reading kana determined by using the shape. It becomes possible to display handwriting input candidates (handwriting input candidates based on reading kana).

  Here, the processing of the block B15 shown in FIG. 17 described above will be described. As described above, the candidate display process is executed each time one stroke is written by hand in the handwriting input area 500. In the following description, for example, stroke data corresponding to the stroke of the nth image in block B11 is used. For the sake of convenience, the keyword searched in the above-described blocks B13 and B14 when “” is input is referred to as an n-th keyword.

  In general, the greater the number of characters (number of strokes), the higher the possibility that the user intends. Therefore, in this embodiment, for example, the number of strokes (that is, the number of strokes) is used as the priority of each keyword. In this case, for example, n is assigned as a priority (value) to the keyword of the nth image, and the priority of the keyword of the nth image is set to n as the priority assigned to the keyword up to the (n-1) th image. The added value. According to this, the priority of the keyword of the nth image can be made higher than the keyword of the n-1th image, for example. Here, the description will be made assuming that the number of strokes is used as the priority of each keyword, but a constant or the like other than the number of strokes may be used.

  Hereinafter, the priority of each keyword will be described in detail with reference to FIGS. Here, as shown in FIG. 18, it is assumed that the character “e” is written by hand with strokes from the first stroke to the third stroke.

  FIG. 18 shows the priority of each keyword when strokes up to the second stroke are written by hand. In the example shown in FIG. 18, it is assumed that the keywords up to the second screen (that is, the first screen keyword and the second screen keyword) are “air conditioner”, “factory”, “achievement”, and “reclaimed”. It is assumed that the priority given to the keyword “air conditioner” by the second stroke is 3. Similarly, it is assumed that the priority given to the keywords “factory” and “achievement” by the second stroke is 2, and the priority given to the keyword “land reclamation” is 1.

  Since the priority assigned to the keyword “air conditioner” is 3, the keyword “air conditioner” is a keyword for the first stroke and a keyword for the second stroke. Further, since the priority given to the keywords “factory” and “achievement” is 2, the keywords “factory” and “achievement” are keywords of the second stroke. Furthermore, since the priority given to the keyword “reclaiming” is 1, the keyword “reclaiming” is the keyword for the first stroke.

  Here, it is assumed that the keywords in the third screen are “air conditioner”, “factory”, “achievement”, and “far-throw”. Note that the keywords “air conditioner”, “factory”, and “achievement” are keywords corresponding to the handwriting input candidates by handwriting described above. The keyword “long throw” is a keyword corresponding to the handwriting input candidate using the above-mentioned reading kana.

  In this case, the keyword “air conditioner”, “factory”, “achievement”, and “far-throw” that are the keywords in the third screen are given priority 3. Thus, the priorities given to the keywords “air conditioner”, “factory”, “achievement”, and “long throw” are added to the priorities given to the keyword up to the second stroke described above.

  FIG. 19 shows the priority of each keyword when the stroke of the third stroke is written by hand.

  First, for the keyword “air conditioner”, the priority assigned to the keyword “air conditioner” by the second stroke is 3, so the priority is 6 when the stroke of the third stroke is written by hand. Become. Similarly, for the keywords “factory” and “achievement”, 3 is added to the priority shown in FIG. 18 (that is, the priority up to the second stroke), and the stroke of the third stroke is written by hand. The priority is 5 respectively. Further, since the keyword “reclaimed” is not the keyword for the third stroke, the priority shown in FIG. 18 is maintained.

  As for the keyword “long throw”, the priority is not given to the keyword “long throw” by the second stroke, so the priority becomes 3 when the stroke of the third stroke is written by hand. .

  As described above, the keyword “long throw” is a keyword corresponding to a handwritten input candidate based on a reading kana, but a keyword corresponding to a handwriting input candidate based on the reading kana is different from a handwritten input candidate (corresponding to) based on a handwriting. If one or more strokes written by hand are not recognized as, for example, katakana characters, they are not searched. Specifically, as shown in FIGS. 18 and 19, for example, the keyword “air conditioner” or the like is searched from the time when the stroke of the first stroke is written by hand, but the keyword “far throw” is the third stroke. The first search is made when the stroke is written by hand.

  That is, for example, even if the user wants to display a handwriting input candidate by reading, the priority of the keyword corresponding to the handwriting input candidate by the reading kana is higher than the keyword corresponding to the handwriting input candidate by another handwriting. As a result, the candidate desired by the user may not be displayed preferentially.

  Therefore, in the present embodiment, a predetermined coefficient is given to a handwriting input candidate (corresponding to a handwriting input candidate) and a handwriting input candidate (a keyword corresponding to a reading kana) based on a handwriting, and the handwriting input candidate based on the handwriting and the reading It is also possible to make the priorities different from those of handwritten input candidates by kana. In the case shown in FIG. 19, the priority of the keyword “long throw” is 6 if the priority of the keyword that is a candidate for handwriting input by reading kana is multiplied by, for example, the coefficient 2. In this case, the coefficient for the handwriting input candidate by handwriting is set to 1, for example. Thus, by making the coefficient for the handwritten input candidate based on the reading kana larger than the coefficient for the handwritten input candidate based on the handwriting, the stroke set (handwriting input candidate based on the reading kana) constituting the keyword “long throw” It becomes possible to preferentially display compared with the keywords “factory” and “achievements” corresponding to handwriting input candidates.

  Here, the coefficient is given to the handwritten input candidate based on the handwriting and the handwritten input candidate based on the reading kana. However, for example, the priority is given to the handwriting input candidate based on the handwriting and the handwriting input candidate based on the reading kana in different ways. You may make it do.

  In the example shown in FIGS. 18 and 19 described above, the keyword “air conditioner” is the keyword for the third stroke, but the keyword “air conditioner” is also searched as a keyword corresponding to a handwriting input candidate by handwriting. The keyword is also retrieved as a keyword corresponding to a handwritten input candidate using a reading kana. In such a case, as described above, when different coefficients are given to the handwritten input candidate based on the handwriting and the handwritten input candidate based on the reading kana, the keyword “air conditioner” is, for example, the handwritten input candidate based on the handwriting (corresponding keyword) Shall be treated as Here, the case where both the handwriting input candidate by handwriting and the handwriting input candidate by reading kana are described as being treated as the handwriting input candidate by handwriting, but in such a case, as the handwriting input candidate by reading kana It may be handled.

  Note that the handwriting input candidate (a set of strokes constituting the corresponding keyword) is displayed in the candidate display area based on the priority assigned to the keyword as described above.

  Next, with reference to FIG. 20, a candidate display area in which handwritten input candidates are displayed will be described in detail. Here, the same parts as those in FIG. 9 described above are denoted by the same reference numerals, and detailed description thereof is omitted.

  As described above, the priority is assigned to each keyword. However, for the sake of convenience, it is assumed below that priority is given to the handwriting input candidate that is a stroke set constituting the keyword. explain.

  As shown in FIG. 20, it is assumed here that the user has handwritten “e” in the handwriting input area 500 on the page editing screen after the character string “package at a nearby electronics store”. In this case, a candidate display area 500a is displayed on the page editing screen. In addition, in this candidate display area 500a, handwritten input candidates are displayed based on the priority at the time when the stroke of the third stroke in the character “d” is written by handwriting.

  In the example illustrated in FIG. 20, the candidate display area 500 a includes the above-described handwriting input candidate having a high priority (value) illustrated in FIG. 19 (that is, a set of strokes constituting a keyword to which a high priority is given) from the top. They are displayed in order.

  Here, the user can select (designate) one of the handwriting input candidates displayed in the candidate display area 500a on the page editing screen shown in FIG. In this way, when one of the handwriting input candidates is selected, the handwriting input candidate is displayed in the handwriting input area 500. FIG. 21 shows an example of the display screen (handwriting input area 500) when “air conditioner” is selected from the handwriting input candidates displayed in the candidate display area 500a. As shown in FIG. 21, the handwriting input candidates are displayed in the handwriting input area 500 in a state adjusted to the size of surrounding characters, for example.

  20 and 21, four handwriting input candidates with high priority are displayed, but other handwriting input candidates such as “pilot” shown in FIG. 19 may be displayed together. Moreover, it is good also as a structure which is displayed only about the handwriting input candidate whose priority is more than a predetermined value.

  20 and 21, all handwriting input candidates are displayed in the same manner, but it is also possible to display the handwriting input candidates based on the handwriting and the handwriting input candidates based on the reading kana described above in a distinguishable manner. It is. Specifically, by displaying handwriting input candidates based on handwriting and handwriting input candidates based on reading kana in different colors, sizes, thicknesses, etc., the user can easily select handwriting input candidates based on handwriting and handwriting input candidates based on reading. Can grasp. In addition, when it corresponds to both the handwriting input candidate by handwriting and the handwriting input candidate by reading kana like the above-mentioned “air conditioner”, it is displayed as a handwriting input candidate by handwriting, for example.

  As described above, in the present embodiment, a stroke set (first stroke set) corresponding to one or more stroke shapes described by handwriting and a reading kana determined by using the one or more stroke shapes are supported. With the configuration in which the stroke set (second stroke set) is displayed as a candidate for handwriting input, the user does not need to write all the character strings by hand when creating a handwritten document, and the user's labor can be reduced. Therefore, the user can easily create a handwritten document. In the present embodiment, for example, even when the kanji cannot be remembered, an appropriate character string can be input by writing the reading kana in handwriting.

  Moreover, in this embodiment, the handwriting input which a user intends more is displayed by displaying a handwriting input candidate (stroke set) according to the priority provided according to the number of one or more strokes described by handwriting. Candidates can be displayed preferentially.

  In the present embodiment, the handwriting input candidate by handwriting and the handwriting input candidate by reading kana are set to a priority obtained by multiplying the number of strokes (number of strokes) by a predetermined coefficient, for example, handwriting input by handwriting. It is possible to adjust the difference in priority generated between the candidate and the handwritten input candidate by reading.

  Further, in the present embodiment, by setting the coefficient for the handwritten input candidate based on the reading kana to be larger than the coefficient for the handwritten input candidate based on the handwriting, the priority of the handwritten input candidate based on the reading pseudonym becomes the priority of the handwritten input candidate based on the handwriting as described above. It is possible to avoid lowering the priority and to preferentially display the handwriting input candidate intended by the user.

  In the present embodiment, the configuration is such that the handwriting input candidate based on the handwriting and the handwriting input candidate based on the reading kana are displayed in a distinguishable manner, so that the user can determine whether the displayed handwriting input candidate is the handwriting input candidate based on the handwriting. It is possible to easily determine whether it is an input candidate.

  Since the processing of the present embodiment can be realized by a computer program, the computer program is installed and executed on a computer through a computer-readable storage medium that stores the computer program, as in the present embodiment. The effect of can be easily realized.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and the equivalents thereof.

  17 ... Touch screen display, 17A ... LCD, 17B ... Touch panel, 17C ... Digitizer, 100 ... Pen, 101 ... CPU, 102 ... System controller, 103 ... Main memory, 104 ... Graphics controller, 105 ... BIOS-ROM, 106 ... Non-volatile 107, wireless communication device, 108 ... EC, 201 ... OS, 202 ... handwritten note application, 301 ... display processing unit, 301A ... handwritten data input unit, 301B ... handwriting drawing unit, 301C ... candidate display processing unit, 302 ... time-series information generation unit, 303 ... editing processing unit, 304 ... page storage processing unit, 305 ... page acquisition processing unit, 306 ... feature amount registration processing unit, 401 ... working memory, 402 ... storage medium.

Claims (15)

Inputting stroke data corresponding to one or more strokes written by hand,
Displaying a plurality of stroke sets identified based on the one or more strokes as candidates for handwriting input,
The plurality of stroke sets include a first stroke set corresponding to the shape of the one or more strokes and a second stroke set corresponding to a reading kana determined using the shape of the one or more strokes.   The method according to claim 1, wherein a plurality of stroke sets are displayed according to a priority given according to the number of the one or more strokes.   The method according to claim 2, wherein priorities for displaying the first stroke set and the second stroke set are different.   The method according to claim 3, wherein the second stroke set has a higher priority for display than the first stroke set.   The method according to claim 1, wherein one or more first stroke sets and one or more second stroke sets are displayed in a distinguishable manner. Input means for inputting stroke data corresponding to one or more strokes written by hand;
Display processing means for displaying a plurality of stroke sets identified based on the one or more strokes as candidates for handwriting input;
Comprising
The plurality of stroke sets includes a first stroke set corresponding to the one or more stroke shapes and a second stroke set corresponding to a reading pseudonym determined using the one or more stroke shapes.   The electronic device according to claim 6, wherein the display processing unit displays a plurality of stroke sets according to a priority given according to the number of the one or more strokes.   The electronic device according to claim 7, wherein priorities for displaying the first stroke set and the second stroke set are different.   The electronic device according to claim 8, wherein the second stroke set has a higher priority for display than the first stroke set.   The electronic device according to claim 6, wherein the display processing unit displays one or more first stroke sets and one or more second stroke sets in a distinguishable manner. A program executed by a computer,
In the computer,
Inputting stroke data corresponding to one or more strokes written by hand,
Displaying a plurality of stroke sets identified based on the one or more strokes as candidates for handwriting input,
The plurality of stroke sets includes a first stroke set corresponding to the shape of the one or more strokes and a second stroke set corresponding to a reading kana determined using the shape of the one or more strokes.   The program according to claim 11, wherein a plurality of stroke sets are displayed according to a priority given according to the number of the one or more strokes.   The program according to claim 12, wherein priorities for displaying the first stroke set and the second stroke set are different.   The program according to claim 13, wherein the second stroke set has a higher priority for display than the first stroke set.   The program according to claim 11, wherein one or more first stroke sets and one or more second stroke sets are displayed in a distinguishable manner.

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