Abstract: Embodiments provide a method and system for audio generation from contextual text input is provided. The disclosure gives due importance to the granularity of the content. The system allows the user to specify the properties of the audio to be generated. Here, context is used to identify the importance of a particular sound over the others and thus automatic adjustments of the audio output to give a more realistic feel. The system generates dataset for training audio models. The user can give input query in natural language and the audio requested will be generated for training and developing the necessary classification or other necessary audio models. The system provides a feature of automated fine-tuning of the model parameters to suit the new automatically collected training data. Furthermore, the system provides a pre-trained inbuilt model repository with audio models belonging to the main categories of noises.

Abstract: Good health is one of the paramount essentials for any human being. A method and system for assessing and improving wellness of a person using body gestures have been provided. The system is configured to address fitness, wellness and physical movement related problems for both the abled and the differently abled society. The disclosure provides an intelligent and adaptive system that will comprehend the gestures and postures of the person to assess his capability of undertaking wellness activities. The person's movement capabilities and the environment are learnt by the system to track the gestures for the activities. Based on his gestures, the extent of activity achievement is calculated. The system also has the feature of provisioning dynamic activities to the person based on prior attempts and levels of achievements. Additionally, the system also providing the fitness routine in an AR environment by human-to-object mapping through object detection and augmentation.

Abstract: Embodiments provide a method and system for audio generation from contextual text input is provided. The disclosure gives due importance to the granularity of the content. The system allows the user to specify the properties of the audio to be generated. Here, context is used to identify the importance of a particular sound over the others and thus automatic adjustments of the audio output to give a more realistic feel. The system generates dataset for training audio models. The user can give input query in natural language and the audio requested will be generated for training and developing the necessary classification or other necessary audio models. The system provides a feature of automated fine-tuning of the model parameters to suit the new automatically collected training data. Furthermore, the system provides a pre-trained inbuilt model repository with audio models belonging to the main categories of noises.

Abstract: This disclosure relates generally to a system and method to identify a plurality of noises or their combination to suppress them and enhancing the deteriorated input signal in a dynamic manner. It identifies noises in the audio signal and categorizing them based on the trained database of noises. A combination of deep neural network (DNN) and artificial Intelligence (AI) helps the system for self-learning to understand and capture noises in the environment and retain the model to reduce noises from the next attempt. The system suppresses unwanted noise coming from the external environment with the help of AI based algorithms, by understanding, differentiating, and enhancing human voice in a live environment. The system will help in the reduction of unwanted noises and enhance the experience of business and public meetings, video conferences, musical events, speech broadcasts etc. that could cause distractions, disturbances and create barriers in the conversation.

Abstract: Augmented Reality is having numerous applications in the field of beverage industry. For example, in preparing cocktails. Conventional methods fail to provide an interactive AR based cocktail preparation, enabling the user to prepare cocktail. The present disclosure analyzes an image of a shelf to obtain a plurality of beverage types. A plurality of potential cocktails are generated based on the analysis and displayed to the user using 3D Augmented Reality (AR). A procedure for preparing a cocktail, requested by the user, is displayed near a located glassware kept by the user using 3D AR. A volume of the glassware is computed and a quantity of each beverage to be added is computed based on the volume. Further, a quantity of each beverage added by the user is dynamically measured by using 3D AR techniques and recommendations are provided to the user if there is any deviation.

Abstract: This disclosure relates generally to a system and method to identify a plurality of noises or their combination to suppress them and enhancing the deteriorated input signal in a dynamic manner. It identifies noises in the audio signal and categorizing them based on the trained database of noises. A combination of deep neural network (DNN) and artificial Intelligence (AI) helps the system for self-learning to understand and capture noises in the environment and retain the model to reduce noises from the next attempt. The system suppresses unwanted noise coming from the external environment with the help of AI based algorithms, by understanding, differentiating, and enhancing human voice in a live environment. The system will help in the reduction of unwanted noises and enhance the experience of business and public meetings, video conferences, musical events, speech broadcasts etc. that could cause distractions, disturbances and create barriers in the conversation.

Abstract: An automated system and method to authenticate one or more users based on capturing one or more images of a set of teeth, obtaining a selected image from the one or more captured images and extracting a portion of the selected image to obtain an extracted image. Each extracted image is converted into a grayscale image and stored in a database along with the username and the user keyword of the one or more users. A unique signature matrix and a pattern vector is generated by processing the grayscale image and stored in the database along with the username. One or more images comprising a set of teeth of at least one user is captured and a unique signature matrix obtained from the same is compared with a set of unique signature matrices previously stored in the database and at least one action is triggered based on the comparison.

Abstract: An automated system and method to authenticate one or more users based on capturing one or more images of a set of teeth, obtaining a selected image from the one or more captured images and extracting a portion of the selected image to obtain an extracted image. Each extracted image is converted into a grayscale image and stored in a database along with the username and the user keyword of the one or more users. A unique signature matrix and a pattern vector is generated by processing the grayscale image and stored in the database along with the username. One or more images comprising a set of teeth of at least one user is captured and a unique signature matrix obtained from the same is compared with a set of unique signature matrices previously stored in the database and at least one action is triggered based on the comparison.