International Business Machines Corporation

Cheng-Yu Yu

Chih-Yuan Lin

Yu-Ning Hsu

I-Hsiang Liao

Ping-Hung Lai

Elaine I H Liao

Hsinchi Chang

Elaine Ih Liao

Yin-Duen Liao

A computer processing system is provided for enhancing video-based language learning. The system includes a video server for storing videos that use one or more languages to be learned. The system further includes a video metadata database for storing translations of sentences uttered in the videos, character profiles of characters appearing in the videos, and mappings between the sentences and a learner profile. The system also includes a learner profile database for storing learner profiles. The system additionally includes a semantic analyzer and matching engine for finding, for at least a given video and a given learner, alternative sentences for and responsive to the translations of the sentences uttered in the given video that conflict with a respective learner profile for the given learner. The computer processing system further includes a presentation system for playing back the given video and providing the alternative sentences to the given learner.

Enhancing video language learning by providing catered context sensitive expressions

A method for dynamically detecting and converting a context-sensitive information in a first language and a first format to a second language and a second format that is understandable to an end user based on a user-specified setting is provided. The method may use a built-in camera of a computing device to dynamically detect and capture an image frame of context-sensitive information. The method may use Optical character recognition (OCR), as well as contextual information such as GPS data available from a mobile computing device, to automatically translate and reformat the context-sensitive information in real-time so a user may understand it unambiguously.

Reformatting of context sensitive data

Software translation quality and efficiency are improved by providing user interface (UI) context for translators. Unicode symbols are used to uniquely tag user-visible strings from the source code and into resource files. Those strings include titles, product names, error messages, strings in images and any other text that may be present on the user interface. Once the 'pseudo' resource files are integrated into a build, automation is run to gather screenshots of the application. Image recognition is then used to link screenshots of the UI in which a resource file string appears, such that screenshots will be brought forward and displayed to the translator when working on translating the user-visible strings of the software being localized.

Automated generation and identification of screenshots for translation reference

A method includes receiving a first virtual board selection from a first user, wherein a first virtual board allows for one or more users to create one or more virtual posts during a current collaboration event. The method displays the first virtual board and a first set of previously created virtual posts in the first virtual board, wherein the first set of previously created virtual posts is associated with a previous collaboration event. The method displays two or more templates for creating a new virtual post. The method receives content to populate the first template, wherein the populated first template represents a first virtual post of a second set of virtual posts for the current collaboration event. The method displays the first virtual post on the first virtual board based on a first position of an electronic device associated with the first user relative to the first virtual board.

Growing community of inventors

Taipei, Taiwan

Cheng-Yu Yu