Abstract: A method and system method for automatic speech recognition using selection of speech models based on input characteristics is disclosed herein. The method includes obtaining speech data from a speaker utilizing a microphone or an audio upload. The system and method select the best speech recognition model to automatically decode the input speech and continuously update models by updating/creating models in a database based on users speech abilities.

Abstract: This invention concerns interactive language learning methods and systems. These interactive systems and methods include an interactive unit, for example, a toy that includes a processor running a language learning application, an output device, e.g., a speaker, to communicate with the learner, a learner input device, e.g., microphone to receive input from the learner, a server running learning software, and, in preferred embodiments, a mobile device configured to control the toy settings. In operation, a user (e.g., the learner's parent) selects the native language used to the unit/toy and initially interacts with the learner (e.g., a child) in the same language. After assessing the learner's native language knowledge, the unit/toy begins interacting with the learner in a second (i.e., non-native or foreign) language selected by the user. The system then exposes the learner to sounds, then syllables and words before gradually progressing to phrases and sentences, followed by stories, assessments, and tasks.

Abstract: A cognitive skill development method and system for training users in various fields wherein data is added to a video and the video is played on a user device in accordance with such data. Video interruption techniques such as video occlusion are used to interrupt the video. The user is then presented with questions corresponding to the video and the user's response to such questions is solicited and recorded.

Abstract: An interactive auditory capacity development method and system for language processing wherein a phonetic element of a language is introduced to a user and the user is then provided with an interactive environment on a device for processing the phonetic element. The processing may include identification and comparison of the phonetic element with other sounds retrieved from a database. The interactive environment evaluates the user input and provides feedback to the user. The device used for providing the interactive environment to the user may include a smart phone, tablet or a physical toy.

Abstract: An interactive cognitive skill improvement method and system is provided wherein a real life video is deployed in a video game environment and interruptions are induced in the real life video to seek a response from a user based on the interruptions. The user is expected to predict a specific outcome or provide a specific response based on the scenario in the real life video. The video game environment is enabled to compare the user's response with the actual outcome in the real life video and the user's performance is analyzed and recorded for future reference.

Abstract: Tear film stability has an important role in the quality of vision. A system and method for performing Fluctuation Analysis of Spatial Image Correlation (FASIC) provides for a non-invasive system and method for evaluating the dynamics of the tear film surface using spatial autocorrelation analysis. With FASIC, a series of images are obtained using illumination and a camera. The spatial autocorrelation is calculated for image frames produced by the camera. A sinusoidal background appears in this correlation together with other features. The changes in the sinusoidal background of the spatial autocorrelation is extracted and monitored over time. The spatial period of this sinusoidal background correlates with the thickness of the tear film. In this regard, one is able to derive the tear film thickness from the period of this sinusoidal background.

Abstract: Tear film stability has an important role in the quality of vision. A system and method for performing Fluctuation Analysis of Spatial Image Correlation (FASIC) provides for a non-invasive system and method for evaluating the dynamics of the tear film surface using spatial autocorrelation analysis. With FASIC, a series of images are obtained using illumination and a camera. The spatial autocorrelation is calculated for image frames produced by the camera. A sinusoidal background appears in this correlation together with other features. The changes in the sinusoidal background of the spatial autocorrelation is extracted and monitored over time. The spatial period of this sinusoidal background correlates with the thickness of the tear film. In this regard, one is able to derive the tear film thickness from the period of this sinusoidal background.