Talent Unlimited Online Services Private Limited

Talent Unlimited Online Services Pr

Sumegha Yadav

Rahul Prasad

Ankit Prasad

Achyut Saxena

The present invention provides systems and methods for dynamic word prediction and suggestion. The method includes an AI engine configured to render a touch-enabled keyboard interface on a display unit of the electronic device, identify a plurality of elements of an input message of a user on a messaging application and transform the input message into an array of a specific numbers based on the plurality of elements. The method further includes converting the array into a 2D matrix of embeddings by the AI engine, wherein the embeddings include semantic information of the input message to identify a context of the input message and converting the matrix into an output array with a changed dimension. The AI engine is further configured to convert the output array into probabilities of one or more words corresponding to the input message of the user on the messaging application.

Artificial intelligence based hybrid system and method for generation of word predictions based on language modelling

A system for generating a contextualized text using a character-based convolutional neural network architecture (CNN) is disclosed. The system includes a memory, a character-based CNN engine having executable modules and a processor configured to execute the character-based CNN engine and the executable modules for generating contextualized text using a character-based convolutional neural network architecture (CNN). The executable modules includes a data processing module for pre-processing an input conversational text data, a corpus builder unit for developing a corpus of most frequent n-grams, a dataset generation module for performing logarithmic mapping of a frequency of a respective n-gram in the corpus for a dataset prepared for training, a training module for training an artificial intelligence (AI) based model with datasets for a predetermined range of epochs and a prediction module for executing the trained AI-based model for predicting characters contextually till an end-of-sentence (EOS) token is found.

System and method for generating contextualized text using a character-based convolutional neural network architecture

The present invention discloses a system and for sentence completion in an edge device. The method comprises receiving input from a user through a user interface (); scrutinizing a length of the received input by a smart sentence composer; sanitizing the received input text and restricting the length of the input text to be within a preset threshold number; splitting the received input text from into letters/words (); predicting several words and a cluster of most probable word's indices by the smart sentence composer (), and wherein the word's indices have a similarity above the preset threshold number; converting the word's indices to words using index to word mapping (); choosing the word/words in the cluster having highest score for prediction (); and the words are continuously predicted until the end of token of word index (), is determined for completing the sentence prediction.

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GURUGRAM, India

Sumegha Yadav