585 results about "Handwriting recognition" patented technology

A word pattern recognition system based on a virtual keyboard layout combines handwriting recognition with a virtual, graphical, or on-screen keyboard to provide a text input method with relative ease of use. The system allows the user to input text quickly with little or no visual attention from the user. The system supports a very large vocabulary of gesture templates in a lexicon, including practically all words needed for a particular user. In addition, the system utilizes various techniques and methods to achieve reliable recognition of a very large gesture vocabulary. Further, the system provides feedback and display methods to help the user effectively use and learn shorthand gestures for words. Word patterns are recognized independent of gesture scale and location. The present system uses language rules to recognize and connect suffixes with a preceding word, allowing users to break complex words into easily remembered segments.

Ink strokes of cursive writing are segmented to make the cursive writing more like print writing, particularly with respect to the number of strokes of a character. A stroke-segmentation module first finds the local extrema points on a stroke of input ink. Then the local extrema points are stepped through, two (or three) at a time. The stroke-segmentation module may compare the three (or four) ink segments that are adjacent to the two (or three) local extrema points to a set of predefined stroke-segmentation patterns to find a closest matching pattern. Strokes are then segmented based on a stroke-segmentation rule that corresponds to the closest matching pattern. Additional stroke segmentation may be performed based on the change of curvature of the segmented ink strokes. Then, a character-recognition module performs character recognition processing by comparing the segmented ink strokes to prototype samples at least some of which have been similarly segmented.

An apparatus for capturing and storing medical emergency information under the adverse circumstances of the emergency scene, without relying on multiple computers and remote communications for support during use. To accomplish data capture and storage, use of a single ruggedized hand held computer with a graphical user interface employing a touch sensitive display screen, and pen stylus for simplifying documentation of patient demographic, history and medications data, focal patient complaints and problems, vital signs, physical exam findings, medication administration, routes and quantities, motorized vehicle crash history, case disposition, emergency crew, and case review and notes. Collection of focal patient complaints and problems is simplified through a body graphical user interface. Easily accessed reference databases for drugs and protocols support the emergency medical technician. Handwriting recognition, signature capture and numerical data entry enable obtaining of necessary crew and patient signatures and other data, including patient refusal of care. Through the use of a variety of secure communication interfaces, printing or transfer of all data collected is provided to other systems. Full compliance with NHTSA and Utstein minimal data reporting set requirements.

A pen-based computer text input system capable of interpreting a special pre-defined set of single stroke glyphs. Each input stroke is identified with one of three categories: (1) pre-character modifier strokes, (2) character or symbol strokes, or (3) post-character modifier strokes. Pre-character modifier strokes precede character strokes and inform the present recognition system that a subsequently entered character stroke is to be modified by the pre-character modifier stroke in a pre-defined manner. Character strokes cause a character or symbol to be displayed on the display device the moment it is input on the writing tablet, interpreted in accordance with any pre-character modifier stroke. A post-character modifier stroke causes the recognition system to modify, in a pre-defined manner, a character or symbol which was previously entered and displayed. An important advantage of the present invention is its ability to provide immediate recognition of multiple stroke characters without using boxed input.

A method, computer program product, and a data processing system for scaling handwritten character input for performing handwriting recognition. A stroke parameter is derived from a handwritten character stroke and an input area is calculated in which the handwritten character stroke was supplied. The stroke parameter is scaled according to the input area.

The present invention proposes the use of a surface or writing surface such as paper and a moveable element such as a pen or a stylus. The stylus comprises an input means such as a charge-coupled device (CCD) or digital camera, a microcomputer, memory, power supply, and a communications device, whereby the digital camera scans the surface for position-related information to determine the position and/or movement of the stylus relative to the surface. The path of stylus is determined by detecting a sequence of position-related information. An output signal from the digital camera or array of light sensitive elements is sent to a computer or processor and finally output to the user. The output can be in various forms including an image on a computer display or a computer printout. When writing on the surface, handwriting recognition software can be used to convert the handwritten text into a "keyboard-typed" representation.

A language recognition system, method and program product for recognizing language based input from computer users on a network of connected computers. Each computer includes at least one user based language model trained for a corresponding user for automatic speech recognition, handwriting recognition, machine translation, gesture recognition or other similar actions that require interpretation of user activities. Network computer users are clustered into classes of similar users according to user similarities such as, nationality, profession, sex, age, etc. User characteristics are collected by sensors and from databases and, then, distributed over the network during user activities. Language models with similarities among similar users on the network are identified. The language models include a language model domain, with similar language models being clustered according to their domains. Language models identified as similar are modified in response to user production activities. After modification of one language model, other identified similar language models are compared and adapted. Also, user data, including information about user activities and language model data, is transmitted over the network to other similar users. Language models are adapted only in response to similar user activities, when these activities are recorded and transmitted over the network. Language models are given a global context based on similar users that are connected together over the network.

The present invention relates to three-dimensional (3D) handwriting recognition methods and systems. The present invention provides a 3D handwriting recognition method and corresponding system which allows to generate 3D motion data by tracking corresponding 3D motion, calculate corresponding 3D coordinates, construct corresponding 3D tracks, derive 2D projection plane based on some strokes 3D tracks of on character, and generate 2D image for handwriting recognition by mapping the 3D tracks onto the said 2D projection plane. The 3D handwriting recognition method according to the present invention can use the processing power of system more efficiently and highly improve the system performance. So that the system can get the final input result in a much shorter time after the user finishes writing a character without a long time waiting between two characters input, thus the user has more pleased and natural input experience.

The dual microprocessor system includes one microprocessor configured to perform wireless telephony functions and another configured to perform personal digital assistant (PDA) functions and other non-telephony functions. A memory system and a digital signal processor (DSP) are shared by the microprocessors. By providing a shared memory system, data required by both data microprocessors is conveniently available to both of the microprocessors and their peripheral components thereby eliminating the need to provide separate memory subsystems and further eliminating the need to transfer data back and forth between the separate memory subsystems. By providing a shared DSP, separate DSP devices need not be provided, yet both microprocessors can take advantage of the processing power of the DSP. In a specific example described herein, the microprocessors selectively program the DSP to perform, for example, vocoder functions, voice recognition functions, handwriting recognition functions, and the like.

A force sensor particularly suited for use in an electronic stylus that senses the contact force on its nib for recording pen strokes and handwriting recognition. The sensor has a housing for a load bearing member for receiving an input force to be sensed and associated circuitry for converting the input force into an output signal indicative of the input force. The bearing member is movably mounted within the elongate body (up to 100 microns). The input force acting on the load bearing member is caused by contact on the nib. The load bearing member is biased against the direction of the input force. The force sensor also has a light source and photo-detector for sensing levels of illumination from the light source. Associated circuitry converts a range of illumination levels sensed by the photo-detector into a range of output signals, so that the illumination level sensed by the photo-detector varies with movement of the load bearing member within the elongate body such that the output signal from the circuitry is indicative of the input force. Using an optical sensor avoids the need to use a delicate piezo-resistive sensor that requires careful tolerancing during production.

Techniques are provided for determining collaborative notes and automatically recognizing speech, handwriting and other type of information. Domain and optional actor/speaker information associated with the support information is determined. An initial automatic speech recognition model is determined based on the domain and/or actor information. The domain and/or actor/speaker language model is used to recognize text in the speech information associated with the support information. Presentation support information such as slides, speaker notes and the like are determined. The semantic overlap between the support information and the salient non-function words in the recognized text and collaborative user feedback information are used to determine relevancy scores for the recognized text. Grammaticality, well formedness, self referential integrity and other features are used to determine correctness scores. Suggested collaborative notes are displayed in the user interface based on the salient non-function words. User actions in the user interface determine feedback signals. Recognition models such as automatic speech recognition, handwriting recognition are determined based on the feedback signals and the correctness and relevance scores.

A hybrid approach to improve handwriting recognition and voice recognition in data process systems is disclosed. In one embodiment, a front end is used to recognize strokes, characters and/or phonemes. The front end returns candidates with relative or absolute probabilities of matching to the input. Based on linguistic characteristics of the language, e.g. alphabetical or ideographic language for the words being entered, e.g. frequency of words and phrases being used, likely part of speech of the word entered, the morphology of the language, or the context in which the word is entered), a back end combines the candidates determined by the front end from inputs for words to match with known words and the probabilities of the use of such words in the current context.

A handwriting recognition apparatus is disclosed. In one embodiment the apparatus comprises an input device having a handwriting input area and configured to input a plurality of strokes constructing a plurality of characters written successively on the handwriting input area, and a recognition device configured to recognize the characters based on the strokes input by the input device, shapes of the strokes constructing two characters which are written successively and positional relations between or among the strokes constructing the two characters, whenever one stroke is input by the input device.

A hybrid approach to improve handwriting recognition and voice recognition in data process systems is disclosed. In one embodiment, a front end is used to recognize strokes, characters and/or phonemes. The front end returns candidates with relative or absolute probabilities of matching to the input. Based on linguistic characteristics of the language, e.g. alphabetical or ideographic language for the words being entered, e.g. frequency of words and phrases being used, likely part of speech of the word entered, the morphology of the language, or the context in which the word is entered), a back end combines the candidates determined by the front end from inputs for words to match with known words and the probabilities of the use of such words in the current context.

The present invention mines or extracts data present during interaction between at least two participants, for example in a chat session, a video session, etc. via the Internet. The data, which can include participant web camera generated video, audio, keyboard typed information, handwriting recognized information, is analyzed. Based upon the analysis, content-dependent information is determined and may be displayed to one or more participants in the chat session. In one aspect, a video foreground based upon a participant's generated video is combined with a customized computer generated background that is based upon data mined from the chat session. The customized background preferably is melded seamlessly with the participant's foreground data, preferably via background substitution that combines RGB video with depth data that predicts what background may substituted with new imagery. Content-based targeted information can include advertisement(s).

A computer-implemented method for providing a candidate list of alternatives for a text selection containing text from multiple input sources, each of which can be stochastic (such as a speech recognition unit, handwriting recognition unit, or input method editor) or non-stochastic (such as a keyboard and mouse). A text component of the text selection may be the result of data processed through a series of stochastic input sources, such as speech input that is converted to text by a speech recognition unit before being used as input into an input method editor. To determine alternatives for the text selection, a stochastic input combiner parses the text selection into text components from different input sources. For each stochastic text component, the combiner retrieves a stochastic model containing alternatives for the text component. If the stochastic text component is the result of a series of stochastic input sources, the combiner derives a stochastic model that accurately reflects the probabilities of the results of the entire series. The combiner creates a list of alternatives for the text selection by combining the stochastic models retrieved. The combiner may revise the list of alternatives by applying natural language principles to the text selection as a whole. The list of alternatives for the text selection is then presented to the user. If the user chooses one of the alternatives, then the word processor replaces the text selection with the chosen candidate.

A handwriting recognition device including a handwriting recognizing component such as a software application running on a microprocessor. A user interface includes a display having a stroke entry field for digitizing and displaying the strokes comprising one or more written characters, and also incorporates a character spacing indicator to indicate a new character entry field with an adjacent new word indicator to indicate a new word entry field. A recognized character display area is on the display substantially adjacent to the stroke entry and display field. The handwriting recognition component includes an output recognition buffer (ORB) for holding and correcting characters while the characters are being displayed in the recognized character display area.