Patent application number | Description | Published |
20110202836 | TYPING ASSISTANCE FOR EDITING - Apparatus and methods are disclosed for providing feedback and guidance to touch screen device users to improve the text entry user experience and performance. According to one embodiment, a method comprises receiving a text entry, receiving input on a touch screen in the form of a first single touch input located over a word of previously entered text, and presenting the user with one or more suggestion candidates indicated possible replacement words related to the selected word. The user can then select one of the suggestion candidates using a second single touch input to replace the selected word with a word associated with the selected suggestion candidate. | 08-18-2011 |
20110202876 | USER-CENTRIC SOFT KEYBOARD PREDICTIVE TECHNOLOGIES - An apparatus and method are disclosed for providing feedback and guidance to touch screen device users to improve text entry user experience and performance by generating input history data including character probabilities, word probabilities, and touch models. According to one embodiment, a method comprises receiving first input data, automatically learning user tendencies based on the first input data to generate input history data, receiving second input data, and generating auto-corrections or suggestion candidates for one or more words of the second input data based on the input history data. The user can then select one of the suggestion candidates to replace a selected word with the selected suggestion candidate. | 08-18-2011 |
20130339283 | STRING PREDICTION - In a mobile device, the text entered by users is analyzed to determine a set of responses commonly entered by users into text applications such as SMS applications in response to received messages. This set of responses is used to provide suggested responses to a user for a currently received message in a soft input panel based on the text of the currently received message. The suggested responses are provided before any characters are provided by the user. After the user provides one or more characters, the suggested responses in the soft input panel are updated. The number of suggested responses displayed to the user in the soft input panel is limited to a total confidence value to reduce user distraction and to allow for easier selection. An undo feature for inadvertent selections of suggested responses is also provided. | 12-19-2013 |
20140032206 | GENERATING STRING PREDICTIONS USING CONTEXTS - In a mobile device, a context is determined for the mobile device. The context is determined based on a variety of characteristics of the mobile device environment including, for example, the current application being used, any contacts that a user of the mobile device is interacting with or having a conversation with, the current date and/or time, a current topic of the conversation, a current style of the conversation, etc. Based on a set of strings associated with the determined context and user generated text, one or more string predictions are generated for the user generated text. The string predictions may be presented to the user as suggested completions of the user generated text. | 01-30-2014 |
20140267045 | Adaptive Language Models for Text Predictions - Adaptive language models for text predictions are described herein. In one or more implementations, text prediction candidates corresponding to detected text characters are generated according to an adaptive language model. The adaptive language model may be configured to include multiple individual language model dictionaries having respective scoring data that is combined together to rank and select prediction candidates for different interaction scenarios. In addition to a pre-defined general population dictionary, the dictionaries may include a personalized dictionary and/or interaction-specific dictionaries that are learned by monitoring a user's typing activity to adapt predictions to the user's style. Combined probabilities for predictions are then computed as a weighted combination of individual probabilities from multiple dictionaries of the adaptive language model. In an implementation, dictionaries corresponding to multiple different languages may be combined to produce multi-lingual predictions. | 09-18-2014 |
20140278349 | Language Model Dictionaries for Text Predictions - Techniques are described to generate text prediction candidates corresponding to detected text characters according to an adaptive language model that includes multiple individual language model dictionaries. Respective scoring data from the dictionaries is combined to select prediction candidates in different interaction scenarios. In an implementation, dictionaries corresponding to multiple different languages are combined to produce multi-lingual predictions. Predictions for different languages may be weighted proportionally according to relative usage by a user. Weights used to combine contributions from multiple dictionaries may also depend upon factors such as how recently a word is used, number of times used, and so forth. Further, the dictionaries may include interaction-specific dictionaries that are learned by monitoring a user's typing activity to adapt predictions to corresponding usage scenarios. Interaction-specific dictionaries may be applied selectively for predictions in respective usage scenarios, including interaction with a particular application, application type, person, contact group, or location. | 09-18-2014 |
20140310213 | USER-CENTRIC SOFT KEYBOARD PREDICTIVE TECHNOLOGIES - An apparatus and method are disclosed for providing feedback and guidance to touch screen device users to improve text entry user experience and performance by generating input history data including character probabilities, word probabilities, and touch models. According to one embodiment, a method comprises receiving first input data, automatically learning user tendencies based on the first input data to generate input history data, receiving second input data, and generating auto-corrections or suggestion candidates for one or more words of the second input data based on the input history data. The user can then select one of the suggestion candidates to replace a selected word with the selected suggestion candidate. | 10-16-2014 |
20140359434 | PROVIDING OUT-OF-DICTIONARY INDICATORS FOR SHAPE WRITING - Disclosed herein are representative embodiments of tools and techniques for providing out-of-dictionary indicators for shape writing. According to one exemplary technique, a first shape-writing shape is received by a touchscreen and a failed recognition event is determined to have occurred for the first shape-writing shape. Also, a second shape-writing shape is received by the touchscreen and a failed recognition event is determined to have occurred for the second shape-writing shape. The first shape-writing shape is compared to the second shape-writing shape. Additionally, at least one out-of-dictionary indicator is provided based on the comparing of the first shape-writing shape to the second shape-writing shape. | 12-04-2014 |
20140365878 | SHAPE WRITING INK TRACE PREDICTION - Disclosed herein are representative embodiments of tools and techniques for providing one or more ink-trace predictions for shape writing. According to one exemplary technique, a portion of a shape-writing shape is received by a touchscreen. Based on the portion of the shape-writing shape, an ink trace is displayed. Also, predicted text is determined. The ink trace corresponding to a first portion of the predicted text. Additionally, an ink-trace prediction is provided connecting the ink trace to at least one or more keyboard keys corresponding to one or more characters of a second portion of the predicted text. | 12-11-2014 |