Kannada Kali

Lalitha L A, Goutham Jason,, Harshith S, Kenneth Jones, Kevin George Thomas

Abstract


This project is an Application to make a user understand and learn the basics of a language. Kannada Kali focuses on the 4 main aspects of language learning: Listening, Reading, Speaking and Writing. While a child learns, detecting real word error is a really difficult task and requires advanced statistical processing, Data Mining and Natural Language Processing (NLP) techniques which we have implemented in this project.

 


Keywords


Natural Language Processing, Convolutional Neural Networks, Sequence Matcher, Spaced Repetition, Django

Full Text:

PDF

References


VII. REFERENCES

Catherine Regina Heil, Jason S. Wu, Joey J. Lee, Torben Schmidt (2016). “A review of mobile language learning applications: trends, challenges and opportunities”, The EUROCALL Review, Volume 24, No. 2, September 2016

Prahallad L., Prahallad K., and Ganapathiraju M., “A simple approach for building transliteration editors for Indian languages,” Journal of Zhejiang University Science, vol. 6A, no. 11, pp. 1354–1361,2005

Anand Arokia Raj, Tanuja Sarkar, Satish Chandra Pammi, Santhosh Yuvaraj, Mohit Bansal, Kishore Prahallad1, Alan W Black, “Text Processing for Text-to-Speech System in Indian Languages.” K. Elissa, “Title of paper if known,” unpublished.

Su Myat Mon, Hla Myo Tun, “Speech-To-Text Conversion (STT) System Using Hidden Markov Model (HMM) “

Peter Norvig, “Artificial Intelligence A Modern Approach-Prentice Hall (2010)”

Google Bolo application, Google LLC press release March 2019

The Chars74k image dataset -http://www.ee.surrey.ac.uk/CVSSP/demos/chars74k/




DOI: https://doi.org/10.26483/ijarcs.v11i0.6606

Refbacks

  • There are currently no refbacks.


Bookmark and Share


Copyright (c) 2020 International Journal of Advanced Research in Computer Science