Job Overview
1. Maintaining documentation & presentation and drafting project proposals and reports as and when needed
2. Developing and maintaining project deliverables under the direction of the senior project manager
3. Handling back-office work (accounts, HR, drafting, communication, filling, and data management)
4. Handling complete end to end recruitment and other HR activities
5. Coordinating with the team members, the senior project manager, and the clients to ensure deliveries and task management
6. Gathering and refining specifications and requirements based on technical needs and conveying it further to the development team
7. Creating and maintaining software documentation
8. Staying plugged into emerging technologies/industry trends and applying them to operations and activities
9. Performing software and tool testing shared by IITB
10. Working on the pipeline of OCR text correction (converting scanned text to digital text, with manual correction of OCRed text)
Only those candidates can apply who:
1. are available for full time (in-office) internship
2. can start the internship between 1st Oct’20 and 5th Nov’20
3. are available for duration of 6 months
4. have relevant skills and interests
1. Must have expertise in team management
2. Must have excellent communication skills
3. Must have English proficiency (spoken and written)
4. Must have Hindi proficiency (spoken and written)
5. Candidates with knowledge of Sanskrit (speaking and reading) will have an added bonus
6. Must have knowledge of MS-Office
7. Must preferably have hands-on experience in data labeling
8. Must have experience in time and resource management
9. Must carry their own laptops
This is an in-office internship & will start in June. Candidates can work from home, till the lockdown is lifted and it is safe to commute to the campus.
Optical Character Recognition (OCR) is the process of converting the document images into an editable electronic format. This has many advantages like data compression, enabling search or edit options in the images/text, and creating the database for other applications like machine translation, speech recognition, and enhancing dictionaries and language models. OCR in Indian languages is quite challenging due to richness in inflections.
Using open-source and commercial OCR systems, we have observed the word error rates (WER) of around 20-50% on printed documents in four different Indic languages. Moreover, developing a highly accurate OCR system with accuracy as high as 90% is not useful unless aided by the mechanism to identify errors. So, we started with the problem of developing “OpenOCRCorrect”, an end-to-end framework for error detection and corrections in Indic-OCR. Our models outperform state-of-the-art results in Error Detection in Indic-OCR for six Indic languages with varied inflections and we have solved the out of vocabulary problem for Error Correction in Indic-OCR in our ICDAR-2017 conference paper. We further improve the results with the help of sub-word embeddings in our ICDAR-2019 conference paper. The demo video for our framework is at https://youtu.be/u9bqUDrGugc (Must watch for applying candidates)
To install the software, you can go to https://github.com/rohitsaluja22/OpenOCRCorrect and follow the instructions given in https://youtu.be/0hcdlF-zn8E
There is an immediate demand to keep the softcopy of the Indian preserved texts. Currently, we are targeting Sanskrit. Although the OCR tools available online do a decent job on English texts, they are not optimized for Indic languages. Thus, developing an OCR model for the same is our concern. The model should be able to detect text with maximum level accuracy and should be able to draw bounding boxes on each line of the text. Further, in the digitization process of such texts, the second step would be spelling correction and formatting of the text detected by the OCR models.