Text editor on python to convert english text to malayalam(Romanization/Transiteration).

Overview

Manglish Text Editor

This is a simple transiteration (romanization ) program which is used to convert manglish to malayalam (converts njaan to ഞാൻ ). It is aimed to help people who have difficulty in typing malayalam and who is good in typing English.

Tkinter is used for text editor creation and simple database lookup along with frequency data is used for the transiteration program.

Requirements

  • The system should have python3 installed. Ths system i tested on python 3.8.
  • The system works on linux and Mac. Minor changes may be required to run this on windows.
  • The code requires tkinter to be installed. pip install tk command can be used for this.

How to use

  • download or clone the repository using command git clone
  • It is recommended to run the code in a separate virtual environment.
  • Get into the main folder manglish_text_editor by cd manglish_text_editor in terminal.
  • When you run the program for the first time the frequency table needs to get created. For that run python3 transiterator.py. Note that it is a time consuming operation.
  • run python3 main.py. This will open the text editor in another window.
  • The text editor is self explanatory.

How it works

The program makes up a database of possible english typings of a malayalam word and then for each user input it tries to find a near match in the database and along with that tries to create the original word.

Text editor image

The text editor is created using python package named tkinter.

Features

  • Text editor in which the typed english(manglish) word will be converted to malayalam on pressing space or enter key.
  • The text editor has options file save, open, save as, new etc.

Future Scope

  1. Improve tokenizing
  2. use a better method to remove noise
  3. Improve learning algorithm
  4. In text editor add malayalam key board, conversion of an entire file at once, Delete file
  5. Give option to the user to select from the possible list of words on backspace press.
  6. Add bold, text space, font, points to the text editor.
  7. Add feature to convert malayalam to manglish.
  8. Add option select all, search, replace etc.

Contributions

  • Pull requests are welcome. If someone wants to contribute to this project can fork and add the Functionalities.
Owner
Merin Rose Tom
Full stack developer | Python programmer
Merin Rose Tom
BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model

BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model

303 Dec 17, 2022
pkuseg多领域中文分词工具; The pkuseg toolkit for multi-domain Chinese word segmentation

pkuseg:一个多领域中文分词工具包 (English Version) pkuseg 是基于论文[Luo et. al, 2019]的工具包。其简单易用,支持细分领域分词,有效提升了分词准确度。 目录 主要亮点 编译和安装 各类分词工具包的性能对比 使用方式 论文引用 作者 常见问题及解答 主要

LancoPKU 6k Dec 29, 2022
Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)

TOPSIS implementation in Python Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) CHING-LAI Hwang and Yoon introduced TOPSIS

Hamed Baziyad 8 Dec 10, 2022
Optimal Transport Tools (OTT), A toolbox for all things Wasserstein.

Optimal Transport Tools (OTT), A toolbox for all things Wasserstein. See full documentation for detailed info on the toolbox. The goal of OTT is to pr

OTT-JAX 255 Dec 26, 2022
Deploying a Text Summarization NLP use case on Docker Container Utilizing Nvidia GPU

GPU Docker NLP Application Deployment Deploying a Text Summarization NLP use case on Docker Container Utilizing Nvidia GPU, to setup the enviroment on

Ritesh Yadav 9 Oct 14, 2022
Associated Repository for "Translation between Molecules and Natural Language"

MolT5: Translation between Molecules and Natural Language Associated repository for "Translation between Molecules and Natural Language". Table of Con

67 Dec 15, 2022
Klexikon: A German Dataset for Joint Summarization and Simplification

Klexikon: A German Dataset for Joint Summarization and Simplification Dennis Aumiller and Michael Gertz Heidelberg University Under submission at LREC

Dennis Aumiller 8 Jan 03, 2023
Study German declensions (dER nettE Mann, ein nettER Mann, mit dEM nettEN Mann, ohne dEN nettEN Mann ...) Generate as many exercises as you want using the incredible power of SPACY!

Study German declensions (dER nettE Mann, ein nettER Mann, mit dEM nettEN Mann, ohne dEN nettEN Mann ...) Generate as many exercises as you want using the incredible power of SPACY!

Hans Alemão 4 Jul 20, 2022
Model for recasing and repunctuating ASR transcripts

Recasing and punctuation model based on Bert Benoit Favre 2021 This system converts a sequence of lowercase tokens without punctuation to a sequence o

Benoit Favre 88 Dec 29, 2022
Must-read papers on improving efficiency for pre-trained language models.

Must-read papers on improving efficiency for pre-trained language models.

Tobias Lee 89 Jan 03, 2023
Code for paper Multitask-Finetuning of Zero-shot Vision-Language Models

Code for paper Multitask-Finetuning of Zero-shot Vision-Language Models

Zhenhailong Wang 2 Jul 15, 2022
ACL22 paper: Imputing Out-of-Vocabulary Embeddings with LOVE Makes Language Models Robust with Little Cost

Imputing Out-of-Vocabulary Embeddings with LOVE Makes Language Models Robust with Little Cost LOVE is accpeted by ACL22 main conference as a long pape

Lihu Chen 32 Jan 03, 2023
Official Stanford NLP Python Library for Many Human Languages

Official Stanford NLP Python Library for Many Human Languages

Stanford NLP 6.4k Jan 02, 2023
TLA - Twitter Linguistic Analysis

TLA - Twitter Linguistic Analysis Tool for linguistic analysis of communities TLA is built using PyTorch, Transformers and several other State-of-the-

Tushar Sarkar 47 Aug 14, 2022
The code from the whylogs workshop in DataTalks.Club on 29 March 2022

whylogs Workshop The code from the whylogs workshop in DataTalks.Club on 29 March 2022 whylogs - The open source standard for data logging (Don't forg

DataTalksClub 12 Sep 05, 2022
NLP Text Classification

多标签文本分类任务 近年来随着深度学习的发展,模型参数的数量飞速增长。为了训练这些参数,需要更大的数据集来避免过拟合。然而,对于大部分NLP任务来说,构建大规模的标注数据集非常困难(成本过高),特别是对于句法和语义相关的任务。相比之下,大规模的未标注语料库的构建则相对容易。为了利用这些数据,我们可以

Jason 1 Nov 11, 2021
An implementation of model parallel GPT-3-like models on GPUs, based on the DeepSpeed library. Designed to be able to train models in the hundreds of billions of parameters or larger.

GPT-NeoX An implementation of model parallel GPT-3-like models on GPUs, based on the DeepSpeed library. Designed to be able to train models in the hun

EleutherAI 3.1k Jan 08, 2023
🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools

🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools

Hugging Face 15k Jan 02, 2023
justCTF [*] 2020 challenges sources

justCTF [*] 2020 This repo contains sources for justCTF [*] 2020 challenges hosted by justCatTheFish. TLDR: Run a challenge with ./run.sh (requires Do

justCatTheFish 25 Dec 27, 2022
Spacy-ginza-ner-webapi - Named Entity Recognition API with spaCy and GiNZA

Named Entity Recognition API with spaCy and GiNZA I wrote a blog post about this

Yuki Okuda 3 Feb 27, 2022