Wipro Limited

Vijay Garg

Manjunath Ramachandra Iyer

Arindam Chatterjee

Kartik Subodh Ballal

Jijith Nadumuri Ravi

Chetan Nichkawde

Kartik Ballal

Disclosed herein is method and system for identifying one or more Places of Interest (PoI) in a natural language system. Word embedding representation for each word in the natural language input are retrieved from a knowledge repository. Further, for each word, Part-of-Speech (POS) tags are tagged, and dependency labels are generated. Subsequently, a PoI tag is assigned to each word based on the word embedding representation, the POS and the dependency labels of each word. Finally, the one or more PoI are identified based on PoI tag assigned to each word. In an embodiment, the method of present disclosure helps in dynamically identifying one or more PoI from natural language text utterances in interactive systems, thereby enhancing usability of interaction based intelligent systems.

Method and system for identifying places of interest in a natural language input

Systems and methods for identifying and learning emotions in conversation utterances are described. The system receives at least one of textual utterance data, audio utterance data and visual utterance data. A set of facial expressions are fetched from the visual utterance data. The system annotates the set of facial expressions with corresponding set of emotions using predictive modeling. Upon annotating, labelled data is generated by tagging the textual utterance data and the audio utterance data with the set of emotions. The labelled data along with non-labelled data is fed into self-learning model of the system. The non-labelled data is new textual utterance data. The self-learning model learns, from the labelled data, about the set of emotions. Further, the self-learning model also determines a new set of emotions corresponding to the new textual utterance data by using recurrent neural network. The self-learning model generates new labelled data and update itself accordingly.

Integrated system and a method of identifying and learning emotions in conversation utterances

Embodiments of the present disclosure disclose a method and a device for dynamically controlling quality of a video displaying on a display associated to an electronic device is provided. The method comprises detecting current eye position of a user and identifying at least one region of interest (ROI) on a display screen of the display device based on the current eye position of the user. Then, the method comprises predicting next position of the eye based on at least one of the current eye position of the user or the at least one ROI. Also, the method comprises converting the SD video in to a high definition (HD) video displayed on the ROI on the display screen associated with the current and next position of the eye. Further, the method comprises displaying the HD video on the ROI of the display screen.

Growing community of inventors

Pune, India

Vijay Garg