Due to the fast-paced nature of the digital conversation, it is necessary to save as much as time possible while typing. Hence a predictive text application is necessary for this. The objective of this software is to deliver relevant next word prediction based on users typing history.
- We provided a novel in txt format as a dataset
- Using keras library, it analyses sequences of words appearing in the dataset.
- These sequences are then passed into a neural network including LSTM that understands and learns to predict next word based on certain input.
- The model predicts next words upto 25 characters based on the dataset provided and the words typed by the user.
- Predicting the most probable word for immediate selection is one of the most valuable technique for enhancing the communication experience. With growth in mobile technologies and vast spread of the internet, socializing has become much easier. People around the world spend more and more time on their mobile devices for email, social networking, banking and a variety of other activities .
- This can be used in keyboard software’s to predict what the user will type next and suggest the same based on the users historical typing data and thus reducing typing efforts for the user.
Key values / Achievements
- The model was capable to predict the next word based upon its training.
- The screenshots attached demonstrates how the model predicts next few words that user might type.