Patent Application
20200409474
Predictive auto-complete text entry is a function implemented in some text handling tools to automatically complete the text of a word after only a limited amount of text entry, as little as 1 to 3 keystrokes in some cases. Predictive auto-complete text entry tools save the user time by having the user enter fewer keystrokes in order to enter a full word. Such tools are particularly valuable for text intensive applications (e.g., word processing applications, electronic mail applications), particularly considering the relatively small keyboard featured on portable devices. Predictive auto-complete text entry may also be referred to as “word completion” or “inline prediction.” Predictive auto-complete text entry improves efficiency of text entry (i.e., improves speed and reduces errors) by reducing the number of characters that must be entered by the user.
This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Methods, apparatuses, and computer program products are provided that enable a user to enter an acceptance command to accept text suggestions expected by the user even though not yet displayed. In aspects, abbreviated text is entered by the user, which may correspond to a complete text of a greater number of characters, such as a complete word or a complete phrase. The user may also enter an acceptance input via a predetermined key or key combination that signals the user's acceptance of a text suggestion even though that text suggestion may not have been generated or displayed to the user in a user interface. Once the acceptance input is received, the text suggestion may be displayed in the user interface as a complete text that includes the abbreviated text.
In one implementation, a first keyboard input event and a second keyboard input event are received at an electronic device. The first keyboard input event may be interpreted as a first character input and the second keyboard input event may be interpreted as an acceptance input. In response to at least the acceptance input, a first complete word or phrase may be displayed in a graphical user interface, the complete word or phrase including the first character input and a portion not having been presented in the graphical user interface prior to receipt of the acceptance input.
Further features and advantages, as well as the structure and operation of various examples, are described in detail below with reference to the accompanying drawings. It is noted that the ideas and techniques are not limited to the specific examples described herein. Such examples are presented herein for illustrative purposes only. Additional examples will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein.
The accompanying drawings, which are incorporated herein and form a part of the specification, illustrate embodiments of the present application and, together with the description, further serve to explain the principles of the embodiments and to enable a person skilled in the pertinent art to make and use the embodiments.
The features and advantages of embodiments will become more apparent from the detailed description set forth below when taken in conjunction with the drawings, in which like reference characters identify corresponding elements throughout. In the drawings, like reference numbers generally indicate identical, functionally similar, and/or structurally similar elements. The drawing in which an element first appears is indicated by the leftmost digit(s) in the corresponding reference number.
The following detailed description discloses numerous embodiments. The scope of the present patent application is not limited to the disclosed embodiments, but also encompasses combinations of the disclosed embodiments, as well as modifications to the disclosed embodiments.
References in the specification to “one embodiment,” “an embodiment,” “an example embodiment,” etc., indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to effect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.
Numerous exemplary embodiments are described as follows. It is noted that any section/subsection headings provided herein are not intended to be limiting. Embodiments are described throughout this document, and any type of embodiment may be included under any section/subsection. Furthermore, embodiments disclosed in any section/subsection may be combined with any other embodiments described in the same section/subsection and/or a different section/subsection in any manner.
The example embodiments described herein are provided for illustrative purposes and are not limiting. The examples described herein may be adapted to any type of predictive auto-complete text entry system. Further structural and operational embodiments, including modifications/alterations, will become apparent to persons skilled in the relevant art(s) from the teachings herein.
Predictive auto-complete text entry is a function implemented in some text handling tools to automatically complete the text of a word or phrase after only a limited amount of text entry, as little as 1 to 3 keystrokes in some cases. Predictive auto-complete text entry tools save the user time by having the user enter fewer keystrokes in order to enter a full word or phrase. Predictive auto-complete text entry may also be referred to as “word completion” or “inline prediction” as the graphical placement of the text suggestion or text prediction may be within a body of a document or page. Predictive auto-complete text entry improves efficiency of text entry (i.e., improves speed and reduces errors) by reducing the number of characters that must be entered.
For example, a user may enter an abbreviated text (e.g., three keystrokes that may correspond to three characters), and the user may then see a complete word or phrase displayed in a user interface. At that point, the user may enter an acceptance input (e.g., a predetermined key such as any one of a Tab, Space or Enter key) to indicate the user's acceptance of the suggested text. Text suggestions are generated and displayed based on statistics and probabilities given current and preceding user inputs, user data, language models, etc., and may be displayed in a manner that differentiates the text suggestion from entered or previously accepted content. Sometimes, text suggestions are not always displayed or even determined, for example, to save processing cycles or bandwidth, to avoid distracting the user with a text suggestion that is not associated with a high confidence level, or to be more efficient because the benefit of auto-complete text entry may be low (e.g., few keystrokes saved considering the typing speed of the user).
However, as the user becomes accustomed to using predictive auto-complete text entry, the user may expect a text suggestion to always be provided, especially if one has been in the past for a particular abbreviated text. For example, the user may enter the abbreviated text and then the acceptance input regardless whether a text suggestion has been displayed in the user interface. In this case, the user is essentially requesting a text suggestion. If the user enters the acceptance input and no text suggestion is displayed and a tab/space/line return is inserted instead, this creates a disruptive and jarring experience for the user. Thus, to enable smooth and effortless use of inline predictions, it is advantageous to manage this case, in which the user expects a text suggestion to be provided. In one embodiment, when a text suggestion is available but not yet displayed, the acceptance input may be processed as if the text suggestion has been displayed, and the available text suggestion is deemed “accepted” and is displayed as such to the user. In another embodiment, when a text suggestion has not been generated, then a text suggestion request may be made, and the text suggestion may be displayed as “accepted” when it is ready. In either embodiment, when the text suggestion is accepted, the sequencing of the acceptance and the receiving of any further keystrokes may be maintained to ensure the accurate word or phrase is displayed.
Embodiments described herein enable an improved user experience with predictive auto-complete text entry. The user experience is improved when inline predictions are provided when they are most useful or likely to be accepted by the user or upon implicit (e.g., by entering the acceptance input) or explicit request of the user. Moreover, the functioning of the computing device and associated systems is also improved. For example, fewer computing resources (e.g., processor cycles, power, bandwidth) may be required than normal in providing inline predictions selectively rather than continuously, while still allowing for on-demand inline predictions. Processor cycles of the device of the user may be saved if fewer inline predictions are determined and/or displayed. Power may also similarly be saved. The inline prediction process may be implemented with multiple devices (e.g., in a cloud service implementation), and bandwidth may also be saved with selective inline predictions.
In embodiments, the acceptance of expected text suggestions may be implemented in a device in various ways. For instance,
Computing device 102 may be any type of mobile computer or computing device such as a handheld device (e.g., a Palm® device, a RIM Blackberry® device, a personal digital assistant (PDA)), a desktop computer, a laptop computer, a notebook computer, a tablet computer (e.g., an Apple iPad™, a Microsoft Surface™, etc.), a netbook, a mobile phone (e.g., a smart phone such as an Apple iPhone, a Google Android™ phone, a Microsoft Windows® phone, etc.), a wearable device (e.g., virtual reality glasses, helmets, and visors, a wristwatch (e.g., an Apple Watch®)), and other types of computing devices.
Display component 104 is a display of computing device 102 that is used to display text (textual characters, including alphanumeric characters, symbols, etc.) and optionally graphics, to users of computing device 102. The display screen may or may not be touch sensitive. Display component 104 may be an LED (light emitting diode)-type display, an OLED (organic light emitting diode)-type display, an LCD (liquid crystal display)-type display, a plasma display, or other type of display that may or may not be backlit.
Text acceptor 110 is configured to receive abbreviated text 114 provided by a user to computing device 102 via a keyboard (e.g., a virtual keyboard displayed in user interface 106 or keyboard 116). Computing device 102 may include and/or communicatively connected to one or more user input devices, such as physical keyboard 116, a thumb wheel, a pointing device, a roller ball, a stick pointer, a touch sensitive display, any number of virtual interface elements (e.g., such as a virtual keyboard or other user interface element displayed in user interface 106 by display component 104), and/or other user interface elements described elsewhere herein or otherwise known. In an embodiment, computing device 102 may include a haptic interface configured to interface computing device 102 with the user by the sense of touch, by applying forces, vibrations and/or motions to the user. For example, the user of computing device 102 may wear a glove or other prosthesis to provide the haptic contact. Keyboard 116 may include a plurality of user-actuatable components, such as buttons or keys with marks engraved or imprinted thereon, such as letters (e.g., A-Z), numbers (e.g., 0-9), punctuation marks (e.g., a comma, a period, a hyphen, a bracket, a slash), symbols (e.g., @, #, $) and special keys that may be associated with actions or act to modify other keys (e.g., Tab, Space, Enter, Caps Lock, Fn, Shift).
Abbreviated text 114 is a portion of a word or phrase, but not the entirety of the word of phrase, that a user is entering via a user input device (e.g., a virtual or physical keyboard) to computing device 102. In an embodiment, text acceptor 110 may store abbreviated text 114 (e.g., in memory or other storage), and provide abbreviated text 114 to display component 104 for display as shown in
In an embodiment, user interface 106 is a graphic user interface (GUI) that includes a display region in which text 108 may be displayed. For instance, user interface 106 may be a graphical window of a word processing tool, an electronic mail (email) editor, or a messaging tool in which text may be displayed. User interface 106 may optionally be generated by text acceptor 110 for display by display component 104. In an embodiment, when providing abbreviated text 114 to display component 104 for display, text acceptor 110 may also provide indications or other information to identify a completed version of abbreviated text 114 (e.g., a word or phrase that the user is in the process of entering), such that display component 104 may render abbreviated text 114 in a manner that is different from other text. For example, when abbreviated text 114 is displayed in user interface 106 as text 108, the character corresponding to each keystroke being entered may be displayed in contrasting bold levels, different colors or shades, and/or otherwise rendered to permit a visual differentiation from other text.
In an embodiment, as noted above, text intelligence system 112 may receive abbreviated text 114 from text acceptor 110. In embodiments, text intelligence system 112 may be separate from text acceptor 110 (as shown in
In an embodiment, and as described in greater detail below, text intelligence system 112 may be configured to receive abbreviated text 114 from text acceptor 110, and probabilistically determine one or more complete words or phrases likely to correspond to abbreviated text 114. Text intelligence system 112 may receive additional information (e.g., previous keystrokes) from text acceptor 110 to determine a text suggestion. For instance, in an embodiment, text intelligence system 112 may automatically receive abbreviated text 114 and determine whether a text suggestion should be determined, and if a text suggestion is to be generated, what the text suggestion should be for abbreviated text 114. In another embodiment, text acceptor 110 may determine whether a text suggestion should be generated and may request text intelligence system 112 for a text suggestion when one is needed.
As shown in
In embodiments, text acceptor 110 of computing device 102 may enable text acceptance in various ways. For instance,
Flowchart 200 is an example method for managing the acceptance of expected text suggestions. Flowchart 200 begins at step 202. At step 202, a first keyboard input event and a second keyboard input event are received at an electronic device. For example, and with reference to system 100 of
Continuing at step 204 of flowchart 200, the first keyboard input event is interpreted as a first character input. For example, text acceptor 110 may interpret the first keyboard input event, which may be received as abbreviated text 114 from the user typing a first keystroke on keyboard 116, as a first character input. A character input may include a letter, number, or a non-alphanumeric key, such as a punctuation mark or a symbol.
At step 206 of flowchart 200, the second keyboard input event is interpreted as an acceptance input. For example, text acceptor 110 may interpret the second keyboard input event, which may also be received as abbreviated text 114 from the user typing a second keystroke on keyboard 116, as an acceptance input. In embodiments, certain key or key combinations, such as Tab, Enter, Space, Alt and Shift, may be configured by the user or system to be interpreted as an acceptance input. In other embodiments, the acceptance input may be indicated via an audio command or a gesture from the user captured by a user input device, such as a voice recorder, video camera, or the like. In further embodiments, the acceptance key may be a key on the keyboard configured or specifically designed to be the acceptance key. The acceptance input may be a signal indicating that the user desires to accept a text suggestion, which may or may not have been displayed by display component 104 in user interface 106, as shown in
As the acceptance key may be system or user configurable, the acceptance key may have the sole function of being the acceptance key or it may function as the acceptance key when the appropriate condition(s) exist. For example, if the user enters the Tab key in the middle of a word (e.g., the user types several characters that do not form a complete word in English, for example, and then immediately strikes the Tab key), that Tab key input may be interpreted as an acceptance input. In this example, the condition is the acceptance input being received before the completion of a word. Thus, it is more likely that the user desires an insertion of a text suggestion than the user wanting to advance the cursor to the next tab stop or the next field. However, if the user has just finished typing a complete word, phrase or sentence (e.g., indicated by a space, comma or period following a word), and then strikes the Tab key, that Tab key may be interpreted according to its native functionality rather than as an acceptance input. In this example, the condition is the acceptance input being received after the completion of a word, phrase or sentence. In an embodiment, a keyboard input corresponding to a key is interpreted as an acceptance input only when it is entered mid-word or mid-phrase, and in the absence of this condition, that key may be interpreted according to its native functionality. Other rules and heuristics may be utilized to determine when an acceptance key is triggered as such.
In addition, in operation, a text suggestion may be displayed to the user only temporarily and may be converted to an accepted state or may disappear after a predetermined period of time or after the user starts typing through in disregard of the text suggestion. In an embodiment while a text suggestion is being displayed to the user, the acceptance key may be placed in a suspended state such that it may only be utilized as an acceptance input while its default or native functionality is temporarily suspended. When the text suggestion is no longer displayed in the user interface, the acceptance key may regain its native functionality. There may be an overriding measure provided, for example, if the user strikes the acceptance key twice mid-word, then the acceptance key may be interpreted according to its native functionality rather than as an acceptance input. As another overriding measure example, if the acceptance key is pressed and held for a predetermined period of time (e.g., longer than ⅓ of a second) then it may be interpreted according to its native functionality. Other overriding input may be utilized or configured by the system or user. In addition, a default interpretation may also be provided, for example, text acceptor 110 may interpret a key according to the native functionality of that key when there is some ambiguity about which input (e.g., default function input or acceptance input) is desired by the user. There may also be UI provided in the case of ambiguity, providing the two options, where e.g. one option is selected by waiting, and the other by pressing the acceptance key.
Flowchart 200 concludes at step 208, in which based at least on the acceptance input, a complete word or phrase is displayed in a graphical user interface (GUI), the complete word or phrase comprising the character input and a portion not having been presented in the GUI prior to receipt of the acceptance input. For example, as shown in
In the foregoing discussion of flowchart 200, it should be understood that at times, the steps of flowchart 200 may be performed in a different order or even contemporaneously with other steps. For example, the receiving of a first keyboard input event and a second keyboard input event may be performed as different steps, or the interpreting the keyboard input events may be performed contemporaneously. Other operational embodiments will be apparent to persons skilled in the relevant art(s). Note also that the foregoing description of the operation of system 100 is provided for illustration only, and embodiments of system 100 may comprise different hardware and/or software, and may operate in manners different than described above.
For example,
Processing circuits 302 may include one or more microprocessors, each of which may include one or more central processing units (CPUs) or microprocessor cores. Processing circuits 302 may also include a microcontroller, application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), and/or other processing circuitry. Processing circuit(s) 302 may operate in a well-known manner to execute computer programs (also referred to herein as computer program logic). The execution of such computer program logic may cause processing circuit(s) 302 to perform operations, including operations that will be described herein. Each component of computing device 300, such as memory devices 304 may be connected to processing circuits 302 via one or more suitable interfaces.
Memory devices 304 include one or more volatile and/or non-volatile memory devices. Memory devices 304 store a number of software components (also referred to as computer programs), including a text 306 that may be implemented as text acceptor 110 shown in
In an embodiment, text acceptor 306 may be configured in various ways to perform the steps associated with flowchart 200 described above. For instance,
Text input receiver 402 is configured to receive abbreviated text 410 (e.g., according to step 202 of
Text input interpreter 404 is configured to interpret signal 412, which includes input data that corresponds to abbreviated text 410. For example, text input interpreter may access information obtained from keyboard 116, stored in memory (e.g., memory devices 304 of computing device 300 shown in
Acceptance manager 406 is configured to receive signal 414 and based at least on that, determine whether a text suggestion should be generated for abbreviated text 114. In some cases, if the user is typing too fast, it may not be worth it to expend resources to generate a text suggestion because the amount of text saved (e.g., the number of keystrokes saved by the user) with the text suggestion is too small. As a simple example, for a three-letter word, it may not be useful to determine a text suggestion because by the time the text suggestion is displayed to the user, the user may have already finished typing the word. Similarly, for the same example, if a text suggestion is shown after the second keystroke, the user may still have to enter a third keystroke to signal acceptance of the text suggestion (e.g., a Tab key input), and thus no keystroke is saved for that three-letter word. In an embodiment, the determination of whether a text suggestion should be generated may be determined by text intelligence system 408.
If it is determined that a text suggestion should be generated, acceptance manager is configured to determine a text suggestion 416 based at least on signal 414. In an embodiment, text suggestion 416 may be a full or complete text version of abbreviated text 410 received from the user via text acceptor. For example, text suggestion 416 may be a partial word or phrase and thus may be combined with abbreviated text 410 to form a complete or full-text word or phrase. As another example, text suggestion 416 may be a complete word or phrase that may replace abbreviated text 410 when displayed on a GUI. In an embodiment, acceptance manager 406 may forward signal 414 to text intelligence system 408, and any other data useful to determine a text suggestion (e.g., previous keystrokes or words entered by the user, user data pertaining to user typing speed, typing preferences or other behavioral data with respect to typing or how the user interacts with a particular device) and text intelligence system 408 may determine a text suggestion based at least on signal 414. The text suggestion from text intelligence system 408 may be transmitted to acceptance manager 406 to provide to a display component (e.g., display component 104 of
Text intelligence system 408 is shown as being separate from text acceptor 306, but may be implemented as part of text acceptor 306 or as a system on a separate device from the device that includes text acceptor 306. For example, text intelligence system 408 may be implemented in a cloud predictive auto-complete text service. In an embodiment, text intelligence system 408 may be implemented as text intelligence system 112 shown in
For example, text intelligence system 408 may include or utilize a language model, an error model, and UI components to respectively generate text suggestion, correct any error, and enable display of text to the user, for example, via display component 104 of
In embodiments, text intelligence system 408 may generate a text suggestion with a corresponding probability that indicates a likelihood of the text suggestion being the correct text (e.g., word, phrase) that the user is trying to type. For example, for abbreviated text 410, text intelligence system 408 may generate a set of text suggestions that contains the five most likely words. In an embodiment, the set may consist of a predetermined number of tuples, each tuple having the form (word, word_probability), where word is the complete (full-text) word, and word_probability is the probability that the text entered by the user corresponds to that word. Thus, if abbreviated text 410 includes “ha” the set of text suggestions could be: [(“hand”, p1), (“hair”, p2), (“happy”, p3), (“happiness”, p4), (“harp”, p5)], where p1-p5 are the conditional probabilities corresponding to each word.
To determine the word_probability for each tuple in the set, text intelligence system 408 may use word lists, character-, syllable-, morpheme- or word-based language models that provide the probability of encountering words, and using methods known in the art, such as a table lookup, hash maps, tries, neural networks, Bayesian networks and the like, to find exact or fuzzy matches for a given abbreviated text. In embodiments, language models and algorithms work with words or parts of words, and can encode the likelihood of seeing another word or part of word after another based on specific words, word classes (such as “sports”), parts-of-speech (such as “noun”), or more complex sequences of such parts, for example, grammatical models, neural network models, such as Recurrent Neural Networks or Convolutional Neural Networks. In embodiments, the user data may be used in generating the word probability (e.g., the type or length of inline predictions that the user has accepted or typed through in the past, typing speed or typing tendencies, instances when the inline predictions have been rejected, etc.).
Text intelligence system 408 may also determine a phrase probability that indicates the likelihood of text suggestion being the correct phrase that the user is trying to type. The phrase probability may be based on the word probability for a particular abbreviated text. Similar to the set of word probabilities described above, the set of phrase probabilities may consist of a number of tuples, each tuple having the form (phrase, phrase_probability) where phrase is the complete phrase, and phrase_probability is the probability that the received abbreviated text corresponds to that phrase. Text intelligence system 408 may use word probabilities and algorithms, or phrase-based language models to determine likely matches for sequences of words based on the likelihood of the transition from one word to another. Such likelihood may be based on phrase lists and language models that provide the probability of encountering particular word sequences. The word probabilities and/or language models may not only encode the likelihood of seeing another word based on specific adjacent words, but also consider word classes (such as “sports”), parts-of-speech (such as “noun”), or more complex sequences of such parts, such as in grammar models or neural network models, such as Recurrent Neural Networks or Convolutional Neural Networks.
It should be noted that the sets and tuples described herein are merely exemplary, and no particular data structure, data format or processing should be inferred. In embodiments, receipt of abbreviated text 410 may occur continuously and the processing of abbreviated text 410 may occur as each keyboard input event is received. That is, as more keyboard input events are received, the word and/or phrase probabilities may be assessed and updated in real-time. For example, the determining or updating of word probabilities based on the most recently received keyboard input events may occur while the set of phrase probabilities is still being determined based on prior input.
In an embodiment, the word or phrase with the highest probability may be selected as the likely candidate and the text suggestion may be provided based on that word or phrase (e.g., a portion of that word or phrase may be provided as the text suggestion to account for the abbreviated text already displayed). In another embodiment, the word or phrase with the highest probability may not be selected as the likely candidate unless that highest probability is higher than a predetermined threshold and/or the highest probability is higher than the next highest probability by a certain delta amount (e.g., 10%). Thus, an absolute threshold as well as a relative threshold may be utilized. These thresholds may not be static. That is, the thresholds may change over time as text acceptor 306 and/or text intelligence system 408 learn more about the user and his/her interaction with the inline prediction process.
In an embodiment, acceptance manager 406 may further be configured to determine that a text suggestion has been generated on at least the first character input. For example, acceptance manager 406 may have received a text suggestion from text intelligence system 408 but has not yet provided it to display component 104 (or the display component 104 has not yet displayed the text suggestion) before the acceptance input is received from the user. In this embodiment, acceptance manager 406 may provide the generated text suggestion to display component 104, as shown in
In another embodiment, acceptance manager 406 may further be configured to determine that a text suggestion has not been generated on at least the first character input. For example, a text suggestion may not have been generated because the user is typing too fast and there has not been enough time to generate a text suggestion, a text suggestion may have been deemed to be unnecessary or not beneficial given the existing conditions, multiple text suggestions have been generated but none has been selected as a likely candidate or the probabilities of the multiple text suggestions are too similar to determine a likely candidate, etc. In this embodiment, acceptance manager 406 may request for a text suggestion from text intelligence system 408 based at least on the first character input. When a text suggestion is received from text intelligence system 408, acceptance manager 406 may provide the text suggestion to display component 104 to display in user interface 106, as shown in
In an embodiment, multiple text suggestions may be provided by text intelligence system 408 for display component 104 to display in user interface 106 (shown in
Text acceptor 306 may include other components not shown in
Text suggestions may be displayed in various manners. For instance,
In another instance,
Text acceptor 306 may operate in various ways to enable the acceptance of expected text suggestions.
In step 802, the second keyboard input event is determined to be received at least twice in a predetermined time period. In an embodiment, text input receiver 402 shown in
In step 804, the second keyboard input event is interpreted according to a native functionality of at least one of the Tab key input, the Space key input, or the Enter key input rather than as the acceptance input. In an embodiment, text input interpreter 404 shown in
Text acceptor 306 may operate in another way to enable the acceptance of expected text suggestions. For example, in an embodiment, text acceptor 306 may operate according to one or more steps of flowchart 200, and optionally perform additional steps. For example, embodiments may perform the steps of a flowchart 900 shown in
In step 902, in which it is determined that a text suggestion has been generated on at least the first character input. In an embodiment, acceptance manager 406 shown in
In step 904, the generated text suggestion is provided as the portion for display in the GUI while maintaining a proper sequence of any further keyboard input event. In an embodiment, acceptance manager 406 shown in
Text acceptor 306 may operate in still another way to enable the acceptance of expected text suggestions. For example, in an embodiment, text acceptor 306 may operate according to one or more steps of flowchart 200, and optionally perform additional steps. For example, embodiments may perform the steps of a flowchart 1000 shown in
In step 1002, in which it is determined that a text suggestion has not been generated on at least the first character input. In an embodiment, acceptance manager 406 shown in
In step 1004, the text suggestion is requested from a text intelligence system based at least on the character input. In an embodiment, acceptance manager 406 shown in
In step 1006, the text suggestion is provided as the portion for display in the GUI while maintaining a proper sequence of any further keyboard input event. In an embodiment, acceptance manager 406 shown in
Text acceptor 306 may operate in yet another way to enable the acceptance of expected text suggestions. For example, in an embodiment, text acceptor 306 may operate according to one or more steps of flowchart 200, and optionally perform additional steps. For example, embodiments may perform the steps of a flowchart 1100 shown in
In step 1102, a third keyboard input event is interpreted as a third character input. For example, in an embodiment, text input receiver 402 shown in
In step 1104, multiple text suggestions are received based at least on the third keyboard input from a text intelligence system. For example, in an embodiment, acceptance manager 406 shown in
In step 1106, the multiple text suggestions are provided for presentation on the GUI. For example, in an embodiment, acceptance manager 406 shown in
In step 1108, a user selection of one of the multiple text suggestions is received. For example, in an embodiment, acceptance manager 406 shown in
In step 1110, the user selection is provided as a second portion for a displaying a second complete word or phrase on the GUI. For example, in an embodiment, acceptance manager 406 shown in
In the foregoing discussion of the steps of flowcharts 800-1100, it should be understood that at times, such steps may be performed in a different order or even contemporaneously with other steps. For example, the steps may be performed in a different order or even simultaneously. Other operational embodiments will be apparent to persons skilled in the relevant art(s). Note also that the foregoing general description of the operation of system 100 and/or computing device 300 is provided for illustration only, and embodiments of system 100 and computing device 300 may comprise different hardware and/or software, and may operate in manners different than described above.
Each of display component 104, text acceptor 110, text intelligence system 112, keyboard 116, text acceptor 306, text input receiver 402, text input interpreter 404, acceptance manager 406, and/or text intelligence system 408, and flowcharts 200 and/or 800-1100 may be implemented in hardware, or hardware combined with software and/or firmware. For example, display component 104, text acceptor 110, text intelligence system 112, keyboard 116, text acceptor 306, text input receiver 402, text input interpreter 404, acceptance manager 406, and/or text intelligence system 408, and flowcharts 200 and/or 800-1100 may be implemented as computer program code/instructions configured to be executed in one or more processors and stored in a computer readable storage medium. Alternatively, display component 104, text acceptor 110, text intelligence system 112, keyboard 116, text acceptor 306, text input receiver 402, text input interpreter 404, acceptance manager 406, and/or text intelligence system 408, and flowcharts 200 and/or 800-1100 may be implemented as hardware logic/electrical circuitry.
For instance, in an embodiment, one or more, in any combination, of display component 104, text acceptor 110, text intelligence system 112, keyboard 116, text acceptor 306, text input receiver 402, text input interpreter 404, acceptance manager 406, and/or text intelligence system 408, and flowcharts 200 and/or 800-1100 may be implemented together in a SoC. The SoC may include an integrated circuit chip that includes one or more of a processor (e.g., a central processing unit (CPU), microcontroller, microprocessor, digital signal processor (DSP), etc.), memory, one or more communication interfaces, and/or further circuits, and may optionally execute received program code and/or include embedded firmware to perform functions.
As shown in
Computing device 1200 also has one or more of the following drives: a hard disk drive 1214 for reading from and writing to a hard disk, a magnetic disk drive 1216 for reading from or writing to a removable magnetic disk 1218, and an optical disk drive 1220 for reading from or writing to a removable optical disk 1222 such as a CD ROM, DVD ROM, or other optical media. Hard disk drive 1214, magnetic disk drive 1216, and optical disk drive 1220 are connected to bus 1206 by a hard disk drive interface 1224, a magnetic disk drive interface 1226, and an optical drive interface 1228, respectively. The drives and their associated computer-readable media provide nonvolatile storage of computer-readable instructions, data structures, program modules and other data for the computer. Although a hard disk, a removable magnetic disk and a removable optical disk are described, other types of hardware-based computer-readable storage media can be used to store data, such as flash memory cards, digital video disks, RAMs, ROMs, and other hardware storage media.
A number of program modules may be stored on the hard disk, magnetic disk, optical disk, ROM, or RAM. These programs include operating system 1230, one or more application programs 1232, other programs 1234, and program data 1236. Application programs 1232 or other programs 1234 may include, for example, computer program logic (e.g., computer program code or instructions) for implementing display component 104, text acceptor 110, text intelligence system 112, keyboard 116, text acceptor 306, text input receiver 402, text input interpreter 404, acceptance manager 406, and/or text intelligence system 408, and flowcharts 200 and/or 800-1100 (including any suitable step of flowcharts 200 and/or 800-1100), and/or further embodiments described herein.
A user may enter commands and information into the computing device 1200 through input devices such as keyboard 1238 and pointing device 1240. Other input devices (not shown) may include a microphone, joystick, game pad, satellite dish, scanner, a touch screen and/or touch pad, a voice recognition system to receive voice input, a gesture recognition system to receive gesture input, or the like. These and other input devices are often connected to processor circuit 1202 through a serial port interface 1242 that is coupled to bus 1206, but may be connected by other interfaces, such as a parallel port, game port, or a universal serial bus (USB).
A display screen 1244 is also connected to bus 1206 via an interface, such as a video adapter 1246. Display screen 1244 may be external to, or incorporated in computing device 1200. Display screen 1244 may display information, as well as being a user interface for receiving user commands and/or other information (e.g., by touch, finger gestures, virtual keyboard, etc.). In addition to display screen 1244, computing device 1200 may include other peripheral output devices (not shown) such as speakers and printers.
Computing device 1200 is connected to a network 1248 (e.g., the Internet) through an adaptor or network interface 1250, a modem 1252, or other means for establishing communications over the network. Modem 1252, which may be internal or external, may be connected to bus 1206 via serial port interface 1242, as shown in
As used herein, the terms “computer program medium,” “computer-readable medium,” and “computer-readable storage medium” are used to refer to physical hardware media such as the hard disk associated with hard disk drive 1214, removable magnetic disk 1218, removable optical disk 1222, other physical hardware media such as RAMs, ROMs, flash memory cards, digital video disks, zip disks, MEMs, nanotechnology-based storage devices, and further types of physical/tangible hardware storage media. Such computer-readable storage media are distinguished from and non-overlapping with communication media and propagating signals (do not include communication media and propagating signals). Communication media embodies computer-readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wireless media such as acoustic, RF, infrared and other wireless media, as well as wired media. Embodiments are also directed to such communication media that are separate and non-overlapping with embodiments directed to computer-readable storage media.
As noted above, computer programs and modules (including application programs 1232 and other programs 1234) may be stored on the hard disk, magnetic disk, optical disk, ROM, RAM, or other hardware storage medium. Such computer programs may also be received via network interface 1250, serial port interface 1242, or any other interface type. Such computer programs, when executed or loaded by an application, enable computing device 1200 to implement features of embodiments described herein. Accordingly, such computer programs represent controllers of the computing device 1200.
Embodiments are also directed to computer program products comprising computer code or instructions stored on any computer-readable medium. Such computer program products include hard disk drives, optical disk drives, memory device packages, portable memory sticks, memory cards, and other types of physical storage hardware.
A computer-implemented method for accepting a text suggestion is described herein. The method includes: receiving a first keyboard input event and a second keyboard input event at an electronic device; interpreting the first keyboard input event as a first character input; interpreting the second keyboard input event as an acceptance input; and based at least on the acceptance input, displaying a first complete word or phrase in a graphical user interface (GUI), the complete word or phrase comprising the first character input and a portion not having been presented in the GUI prior to receipt of the acceptance input.
In an embodiment of the foregoing method, the first keyboard input event and the second keyboard input event are physical keyboard input events.
In another embodiment of the foregoing method, the acceptance input comprises at least one of a tab key input, a space key input, or an enter key input.
One embodiment of the foregoing method further comprises determining that the second keyboard input event is received at least twice in a predetermined time period; and interpreting the second keyboard input event according to a native functionality of the at least one of the tab key input, the space key input or the enter key input rather than as the acceptance input.
In another embodiment of the foregoing method, the displaying includes: determining that a text suggestion has been generated on at least the first character input; and providing the generated text suggestion as the portion for displaying in the GUI while maintaining a proper sequence of any further keyboard input event.
In an additional embodiment of the foregoing method, the displaying includes: determining that a text suggestion has not been generated on at least the first character input; requesting the text suggestion from a text intelligence system based at least on the first character input; and providing the text suggestion as the portion for displaying in the GUI while maintaining a proper sequence of any further keyboard input event.
An additional embodiment of the foregoing method further comprises interpreting a third keyboard input event as a third character input; receiving multiple text suggestions based at least on the third character input from a text intelligence system; providing the multiple text suggestions for presentation on the GUI; receiving a user selection of one of the multiple text suggestions; and providing the user selection as a second portion for displaying a second complete word or phrase on the GUI.
A system is described herein. In one embodiment, the system comprises: a processing circuit; and a memory device connected to the processing circuit, the memory device storing program code that is executable by the processing circuit, the program code comprising: a text input receiver configured to receive a first keyboard input event and a second keyboard input event; a text input interpreter configured to interpret the first keyboard input event as a first character input and the second keyboard input event as an acceptance input; and an acceptance manager configured to display a complete word or phrase in a graphical user interface (GUI), the complete word or phrase comprising the first character input and a portion not having been presented in the GUI prior to receipt of the acceptance input.
In an embodiment of the foregoing system, the first keyboard input event and the second keyboard input event are physical keyboard input events.
In another embodiment of the foregoing system, the acceptance input comprises at least one of a tab key input, a space key input, or an enter key input.
In one embodiment of the foregoing system, the text input receiver is further configured to determine that the second keyboard input event is received at least twice in a predetermined time period, and the text input interpreter is further configured to interpret the second keyboard input event according to a native functionality of the at least one of the tab key input, the space key input or the enter key input rather than as the acceptance input.
In another embodiment of the foregoing system, the acceptance manager is further configured to determine that a text suggestion has been generated on at least the first character input; and provide the generated text suggestion as the portion for displaying on the GUI while maintaining a proper sequence of any further keyboard input event.
In yet another embodiment of the foregoing system, the acceptance manager is further configured to determine that a text suggestion has not been generated on at least the first character input; request the text suggestion from a text intelligence system based at least on the first character input; provide the text suggestion as the portion for displaying in the GUI while maintaining a proper sequence of receipt of any further keyboard input event.
In still another embodiment of the foregoing system, the text input interpreter is further configured to interpret a third keyboard input event as a third character input; and the acceptance manager is further configured to receive multiple text suggestions based at least on the third character input from a text intelligence system; provide the multiple text suggestions for presentation on the GUI; receive a user selection of one of the multiple text suggestions; and provide the user selection as a second portion for displaying a second complete word or phrase on the GUI.
A computer program product comprising a computer-readable memory device having computer program logic recorded thereon that when executed by at least one processor of a computing device causes the at least one processor to perform operations is described herein. In one embodiment of the computer program product, the operations comprise: receiving a first keyboard input event and a second keyboard input event at an electronic device; interpreting the first keyboard input event as a first character input; interpreting the second keyboard input event as an acceptance input; and based at least on the acceptance input, displaying a complete word or phrase in a graphical user interface (GUI), the complete word or phrase comprising the first character input and a portion not having been presented in the GUI prior to receipt of the acceptance input.
In an embodiment of the foregoing computer program product, the first keyboard input event and the second keyboard input event are physical keyboard input events.
In another embodiment of the foregoing computer program product, the acceptance input comprises at least one of a tab key input, a space key input, or an enter key input.
In an additional embodiment of the foregoing computer program product, the operations further include: determining that the second keyboard input is received at least twice in a predetermined time period; and interpreting the second keyboard input according to a native functionality of the at least one of the tab key input, the space key input or the enter key input rather than as the acceptance input.
In yet another embodiment of the foregoing computer program product, the displaying further includes: determining that a text suggestion has been generated on at least the first character input; and providing the generated text suggestion as the portion for displaying in the GUI while maintaining a proper sequence of any further keyboard input event.
In yet another embodiment of the foregoing computer program product, the displaying further includes: determining that a text suggestion has not been generated on at least the first character input; requesting for the text suggestion from a text intelligence system based at least on the first character input; and providing the text suggestion as the portion for displaying in the GUI while maintaining a proper sequence of any further keyboard input event.
While various embodiments of the disclosed subject matter have been described above, it should be understood that they have been presented by way of example only, and not limitation. It will be understood by those skilled in the relevant art(s) that various changes in form and details may be made therein without departing from the spirit and scope of the embodiments as defined in the appended claims. Accordingly, the breadth and scope of the disclosed subject matter should not be limited by any of the above-described exemplary embodiments, but should be defined only in accordance with the following claims and their equivalents.
