Advanced Video & NLP Project
Budget: ₹600 – ₹1,500 INR
I have three intertwined tasks that need to move forward together.
First, my raw footage must be shaped into a polished final cut with dynamic transitions, motion graphics, and other advanced effects that keep viewers engaged from start to finish.
Second, I’m compiling an academic paper and require thorough literature gathering, critical analysis, and clear synthesis of recent peer-reviewed sources. Citations should follow APA 7th and be organised in a matrix I can update later.
Finally, the project includes a natural language processing component: automated transcription of the edited videos, keyword extraction, and basic sentiment or topic modelling. Python, spaCy, Hugging Face Transformers, or similar libraries will fit perfectly as long as the code is clean, documented, and reproducible.
Deliverables
• 4K master video (H.264) plus project files
• Literature matrix and 1–2 page synthesis report
• Well-commented NLP scripts/notebooks with sample outputs
Acceptance criteria
• Seamless effects and transitions with consistent colour and audio levels (one revision round included)
• Sources published within the last five years, drawn from databases such as Scopus or Web of Science
• NLP pipeline achieving at least 90 % accuracy on my validation set
A one-month window is available; share your approach and any relevant examples so we can confirm scope and schedule quickly.
First, my raw footage must be shaped into a polished final cut with dynamic transitions, motion graphics, and other advanced effects that keep viewers engaged from start to finish.
Second, I’m compiling an academic paper and require thorough literature gathering, critical analysis, and clear synthesis of recent peer-reviewed sources. Citations should follow APA 7th and be organised in a matrix I can update later.
Finally, the project includes a natural language processing component: automated transcription of the edited videos, keyword extraction, and basic sentiment or topic modelling. Python, spaCy, Hugging Face Transformers, or similar libraries will fit perfectly as long as the code is clean, documented, and reproducible.
Deliverables
• 4K master video (H.264) plus project files
• Literature matrix and 1–2 page synthesis report
• Well-commented NLP scripts/notebooks with sample outputs
Acceptance criteria
• Seamless effects and transitions with consistent colour and audio levels (one revision round included)
• Sources published within the last five years, drawn from databases such as Scopus or Web of Science
• NLP pipeline achieving at least 90 % accuracy on my validation set
A one-month window is available; share your approach and any relevant examples so we can confirm scope and schedule quickly.