One aspect of the present disclosure relates to a method of sentiment analysis based on ambiguity analysis, which includes analyzing information with the sentiment analysis models and the ambiguity analysis models. Another aspect of the present disclosure relates to a method of training the sentiment analysis models and ambiguity analysis models, which includes acquiring information, constructing lexicons, conducting sentiment analysis and ambiguity analysis with said lexicons, acquiring corpus, and training models, etc. Meanwhile, another aspect of the present disclosure relates to a system of sentiment analysis, which includes input, and output modules, acquisition modules, processing modules and database.

One aspect of the present disclosure relates to a method of sentiment analysis based on ambiguity analysis, which includes analyzing information with the sentiment analysis models and the ambiguity analysis models. Another aspect of the present disclosure relates to a method of training the sentiment analysis models and ambiguity analysis models, which includes acquiring information, constructing lexicons, conducting sentiment analysis and ambiguity analysis with said lexicons, acquiring corpus, and training models, etc. Meanwhile, another aspect of the present disclosure relates to a system of sentiment analysis, which includes input, and output modules, acquisition modules, processing modules and database.

The present disclosure is generally directed to systems and methods for executing optical character recognition faster than at least some traditional OCR systems, without sacrificing recognition accuracy. Towards this end, various exemplary embodiments involve the use of a bounding box and a grid-based template to identify certain unique aspects of each of various characters and/or numerals. For example, in one embodiment, the grid-based template can be used to recognize a numeral and/or a character based on a difference in centerline height between the numeral and the character when a monospaced font is used. In another exemplary embodiment, the grid-based template can be used to recognize an individual digit among a plurality of digits based on certain parts of the individual digit being uniquely located in specific portions of the grid-based template.

An electronic communications method includes receiving, by a computing device, electronic information, with the electronic information including handwritten text. The electronic communications method includes analyzing, by the computing device, the electronic information, with the analyzing includes analyzing the handwritten text. The electronic communications method includes generating printed text based on analyzing the handwritten text. The electronic communications method includes generating a converted document with the printed text based on the electronic information.

An electronic communications method includes receiving, by a computing device, electronic information, with the electronic information including handwritten text. The electronic communications method includes analyzing, by the computing device, the electronic information, with the analyzing includes analyzing the handwritten text. The electronic communications method includes generating printed text based on analyzing the handwritten text. The electronic communications method includes generating a converted document with the printed text based on the electronic information

An improved machine learning system is provided. For example, a content management server may provide a digital assessment of a user's handwriting to assess the user's knowledge of a language. The assessment may comprise adaptive technology to help determine initial questions to provide to the user as well as follow-up questions to clarify appropriate remediation content in a particular context. The content management server may also provide real-time analysis, including assessing multiple users at the same time in adjusting the assessment based on the digital input from each of these users. In some examples, the content management server may incorporate handwriting analysis methods to perform object detection and score handwriting input.

A handwritten music sign recognition device (10) has: a touch information obtaining part (21) which obtains, as position information, a position of an input means on a screen every time the input means moves, from when the input means touches the screen until when the input means is moved away therefrom; a vector information creation part (22) which creates attributes of a vector indicating a trace of movement of the input means as vector information based on the position information; and a stroke characteristic amount derivation part (23) which derives a characteristic amount of a stroke based on the vector information included in the stroke information.

Methods, systems, and computer-accessible mediums are described to authenticate a user using a user's handwriting style rather than using the user's signature through adaptive handwriting challenges which are verified using the machine learning technique of a generative adversarial network. An exemplary system, method, and computer-accessible medium can include, for example, receiving at a first entity, a request for authentication of a user associated with a user identifier; sending from the first entity to the user, a first adaptive phrase; receiving at the first entity, a digital representation of a human transcription of the first adaptive phrase; performing an artificial-intelligence based comparison between the received digital representation of the human transcription of the first adaptive phrase and a user-specific computer-generated discriminator or user-specific computer-generated model of the first adaptive phrase; generating a first score based on the comparison; sending from the first entity (i) an authentication message if the first score is equal to or above a pre-determined threshold or (ii) a failure message if the first score is below a pre-determined threshold.

A method for applying a graphic effect in an electronic device. The method includes identifying a stroke constituting a character based on an input sensed through a display of the electronic device, displaying the identified stroke through the display, identifying a language corresponding to the identified stroke, and identifying a variation value for a graphic effect of the displayed stroke based on a complexity of the identified language.

The present disclosure is generally directed to systems and methods for executing optical character recognition faster than at least some traditional OCR systems, without sacrificing recognition accuracy. Towards this end, various exemplary embodiments involve the use of a bounding box and a grid-based template to identify certain unique aspects of each of various characters and/or numerals. For example, in one embodiment, the grid-based template can be used to recognize a numeral and/or a character based on a difference in centerline height between the numeral and the character when a monospaced font is used. In another exemplary embodiment, the grid-based template can be used to recognize an individual digit among a plurality of digits based on certain parts of the individual digit being uniquely located in specific portions of the grid-based template.