Large-Scale Video Transcription with Whisper AI on Google Colab
Budget: $15 – $25 USD
Project Description:
We have a collection of approximately 20,000 English-language MP4 video files, each around 10 minutes in length, stored in Google Drive. We need an experienced Python developer to create a script to transcribe these videos using OpenAI's Whisper speech recognition model.
Key Requirements:
Google Colab Expertise: Strong experience working with Google Colab notebooks, including setting up environments and utilizing GPU resources.
Whisper AI Knowledge: Familiarity with OpenAI's Whisper model, including loading models, transcribing audio, and handling potential errors.
Python Proficiency: Excellent Python coding skills, with a focus on efficient data processing and file management.
Optimization: Ability to optimize the code for large-scale processing, potentially using techniques like parallel processing to speed up transcription.
Project Deliverables:
Python Script: A well-documented Python script that can be run on Google Colab to transcribe the videos.
Instructions: Clear instructions on how to set up the Colab environment, install necessary libraries, and execute the script.
Transcriptions: The resulting transcriptions in a text format (e.g., TXT or SRT).
Ideal Candidate:
Demonstrated experience with Google Colab for machine learning projects.
Proven ability to work with large datasets and optimize code for efficiency.
Strong communication skills and ability to provide clear documentation.
Additional Information:
We are open to discussing the best format for delivering the transcriptions (e.g., individual files, combined file, etc.).
The budget and timeline for this project are negotiable.
To Apply:
Please submit your proposal with:
A brief overview of your experience with Google Colab, Whisper AI, and Python.
Examples of similar projects you have completed.
Your estimated timeline and budget for this project.
We look forward to hearing from you!
Keywords: Python, Google Colab, Whisper AI, Speech Recognition, Video Transcription, Large-Scale Processing, GPU Optimization
We have a collection of approximately 20,000 English-language MP4 video files, each around 10 minutes in length, stored in Google Drive. We need an experienced Python developer to create a script to transcribe these videos using OpenAI's Whisper speech recognition model.
Key Requirements:
Google Colab Expertise: Strong experience working with Google Colab notebooks, including setting up environments and utilizing GPU resources.
Whisper AI Knowledge: Familiarity with OpenAI's Whisper model, including loading models, transcribing audio, and handling potential errors.
Python Proficiency: Excellent Python coding skills, with a focus on efficient data processing and file management.
Optimization: Ability to optimize the code for large-scale processing, potentially using techniques like parallel processing to speed up transcription.
Project Deliverables:
Python Script: A well-documented Python script that can be run on Google Colab to transcribe the videos.
Instructions: Clear instructions on how to set up the Colab environment, install necessary libraries, and execute the script.
Transcriptions: The resulting transcriptions in a text format (e.g., TXT or SRT).
Ideal Candidate:
Demonstrated experience with Google Colab for machine learning projects.
Proven ability to work with large datasets and optimize code for efficiency.
Strong communication skills and ability to provide clear documentation.
Additional Information:
We are open to discussing the best format for delivering the transcriptions (e.g., individual files, combined file, etc.).
The budget and timeline for this project are negotiable.
To Apply:
Please submit your proposal with:
A brief overview of your experience with Google Colab, Whisper AI, and Python.
Examples of similar projects you have completed.
Your estimated timeline and budget for this project.
We look forward to hearing from you!
Keywords: Python, Google Colab, Whisper AI, Speech Recognition, Video Transcription, Large-Scale Processing, GPU Optimization