Tata Consultancy Services Limited

Aswathy Sreelekha Krishna

Robin Tommy

Robin Tommy Kulangara Muriyil

Rinu Michael

Ajithkumar Narayanan Manaparampil

Reshmi Ravindranathan

Anita Pramod Nanadikar

Anil Kumar Sharma

Navin Infant Raj

Anand Gopinath

Athira Krishnan Remadevi

Gireesh Venkataraghavendra Bandlamudi

Sayan Das

Akhil Guthula

Ullas Ravi

Fathima Thasneem

Jobin P Luke

Mridul Sharma

Girija Subramanian

Re-usage of part of object or object is highly important in manufacturing industry as it can drastically reduce cost and time spent on manufacturing. However, lack of proper information about availability of similar parts leads to redesigning of similar part. Existing databases for engineering drawings do not store categorized information due to which performing feature-based search is not possible. Present application provides systems and methods for extracting, digitizing, and using engineering drawing data. The system receives engineering drawing document and extracts text data present in each cell of table provided in document. Once table data is extracted, isometric views and views other than isometric views that are present in document are identified by the system using pretrained machine learning based model. The system further extract view labels and coordinate information from identified views. The information extracted from document is then stored by the system as engineering drawing data for document.

Systems and methods for extracting, digitizing, and using engineering drawing data

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.

System and method for synthetic audio generation

A system and method to create an intelligent cartoon comic strip based on the dynamic content. Herein, the input is conversation-based text or speech files. The system identifies scenes, objects, sequence and flow for generating the comic strip along with gender of characters appearing in the entire conversation. Text is analyzed to create the situational based background image for the scenes that needs to be rendered. Emotion and placement of characters in the scene is decided by the NLP algorithms along with voice emotional and sentimental analysis. Characters are placed in plain canvas and then text dialog is embedded into corresponding text bubbles. Once this image is obtained, it is overlaid on top of the background based on the context. Further, the scenes are joined into a strip of images in a pattern, which depends on the number, and order of scenes, which is decided, based on the input.

Method and system for creating an intelligent cartoon chat strip based on dynamic content

An authentication system and method is provided. The system: (a) provides a keyboard comprising a letters in a m&#xd7;n format, 'm' represents rows, and n represents columns, each row or column includes a sub-set of the letters, (b) provides input receiving identifiers, each input receiving identifier specific to at least one row or column, (c) processes an input on at least one input receiving identifier from the set of input receiving identifiers, (d) identifies a first intended letter from a first sub-set of letters from a corresponding row or column based on the input, (e) repeats steps (c) and (d) until a last intended letter from a last sub-set of letters is identified to obtain intended identified letters, (f) performs a comparison between the intended identified letters with a pre-registered set of letters stored in a memory, and (g) triggers at least one action based on the comparison.

Authentication system and method

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Thiruvananthapuram, India

Aswathy Sreelekha Krishna