Ticket Contents
As part of the BIRD initiative , we aim to create a tool which can speed up the adoption of Same Language Subtitling (SLS) among the content producers for the entire country.
This will ensure that 200M weak readers and 30M readers with accessibility to get regular reading exposure with content having SLS.
This tool will create SRT files by taking a video file and its text file.
We aim for the tool to support the following languages : Tamil, Telugu, Kannada for now.
Goals & Mid-Point Milestone
Goal 1:
Achieve 60% accuracy in timing accuracy of SRT files in Tamil Language.
Achieve 60% accuracy in timing accuracy of SRT files in Telugu Language.
Achieve 60% accuracy in timing accuracy of SRT files in Kannada Language.
Goal 2:
Achieve 70% accuracy in timing accuracy of SRT files in Tamil Language.
Achieve 70% accuracy in timing accuracy of SRT files in Telugu Language.
Achieve 70% accuracy in timing accuracy of SRT files in Kannada Language.
Goal 3:
Achieve 80% accuracy in timing accuracy of SRT files in Tamil Language.
Achieve 80% accuracy in timing accuracy of SRT files in Telugu Language.
Achieve 80% accuracy in timing accuracy of SRT files in Kannada Language.
Goal 4:
Achieve 90% accuracy in timing accuracy of SRT files in Tamil Language.
Achieve 90% accuracy in timing accuracy of SRT files in Telugu Language.
Achieve 90% accuracy in timing accuracy of SRT files in Kannada Language.
The midpoint milestones will be completion of Goal 1 and Goal 2.
Setup/Installation
No response
Expected Outcome
The input will be a video file and its script in text file format. The text will be utf8 encoding.
The output will be an SRT file with timecode for each line of the script.
Acceptance Criteria
We will use the VLC media player to check the time accuracy of the generated SRT file. This will be used to verify the completion of the goals too. We will use multiple video files to check if the tool is versatile.
Implementation Details
Python or any other technical stack.
Mockups/Wireframes
No response
Product Name
Auto Subtitler for Indian Languages
Organisation Name
Planet Read
Domain
Education
Tech Skills Needed
Machine Learning, Python
Mentor(s)
@arvind-planetread
Category
Accessibility, Machine Learning
Ticket Contents
As part of the BIRD initiative , we aim to create a tool which can speed up the adoption of Same Language Subtitling (SLS) among the content producers for the entire country.
This will ensure that 200M weak readers and 30M readers with accessibility to get regular reading exposure with content having SLS.
This tool will create SRT files by taking a video file and its text file.
We aim for the tool to support the following languages : Tamil, Telugu, Kannada for now.
Goals & Mid-Point Milestone
Goal 1:
Achieve 60% accuracy in timing accuracy of SRT files in Tamil Language.
Achieve 60% accuracy in timing accuracy of SRT files in Telugu Language.
Achieve 60% accuracy in timing accuracy of SRT files in Kannada Language.
Goal 2:
Achieve 70% accuracy in timing accuracy of SRT files in Tamil Language.
Achieve 70% accuracy in timing accuracy of SRT files in Telugu Language.
Achieve 70% accuracy in timing accuracy of SRT files in Kannada Language.
Goal 3:
Achieve 80% accuracy in timing accuracy of SRT files in Tamil Language.
Achieve 80% accuracy in timing accuracy of SRT files in Telugu Language.
Achieve 80% accuracy in timing accuracy of SRT files in Kannada Language.
Goal 4:
Achieve 90% accuracy in timing accuracy of SRT files in Tamil Language.
Achieve 90% accuracy in timing accuracy of SRT files in Telugu Language.
Achieve 90% accuracy in timing accuracy of SRT files in Kannada Language.
The midpoint milestones will be completion of Goal 1 and Goal 2.
Setup/Installation
No response
Expected Outcome
The input will be a video file and its script in text file format. The text will be utf8 encoding.
The output will be an SRT file with timecode for each line of the script.
Acceptance Criteria
We will use the VLC media player to check the time accuracy of the generated SRT file. This will be used to verify the completion of the goals too. We will use multiple video files to check if the tool is versatile.
Implementation Details
Python or any other technical stack.
Mockups/Wireframes
No response
Product Name
Auto Subtitler for Indian Languages
Organisation Name
Planet Read
Domain
Education
Tech Skills Needed
Machine Learning, Python
Mentor(s)
@arvind-planetread
Category
Accessibility, Machine Learning