Generate Subtitles for Long Videos (in English, Java)

The project is designed to handle multiple large video/audio files efficiently by breaking them into segments and processing them concurrently with Java.

Usage

1. Put all videos in a single folder
2. Replace FOLDER value with the video folder(in step 1) path in Util.java.
3. Run SubtitleGenerator.Main.
4. Srt file will be generated in same folder(in step 1) with same file name as its corresponding video.
5. Check log info that has Complete with (0) ..., the number in parentheses indicates how many segments Whisper AI failed to transcribe. A video has video_length_in_seconds/MAX_SEGMENT_DURATION_SECONDS segments.

Key Features

• Producer-Consumer Design:
  • (Deprecated)Optimized the Thread Pool and Blocking Queue to implement a producer-consumer design with thread-safety, ensuring an efficient and stable workflow.
• Multithreaded Implementation:
  • Utilizes multithreading structure to operate audio segments and make multiple transcription requests in parallel in order to ensure efficiency and likely ended with at least 15x speedups.
• Semaphore Design:
  • Applied semaphore to ensure a handled workflow arrangement with great success rate in multi-threaded environment.
• Audio Extraction:
  • Extracts audio from video files and prepares them for transcription.
• Handling multiple Files:
  • Processing all videos in one folder simultaneously, get rid of serial processing.
• Handling Large Files:
  • Automatically splits audio files into smaller segments (e.g., 1-minute chunks) to avoid API size limitations.
• Subtitle Generation:
  • Combines transcriptions of each audio segment into a single .srt subtitle file.
• Cloudflare Workers Integration:
  • Leverages Cloudflare Workers AI for secure and scalable serverless processing of API requests.
• OpenAI Whisper (Speech-to-Text) model Integration:
  • Brings AI integrations with Speech-to-Text power.

Project Highlights

• Multi-Large Videos:
  • Capable of handling multiple, large video/audio files simultaneously.
• Trained Performance:
  • Tuned auto retry mechanism, semaphore and threads to ensure high efficiency, accuracy, and stability.
• Efficiency:
  • Uses multithreading and concurrency features in Java to improve the efficiency of API requests and overall processing speed.
• API Integration:
  • Integrates with Cloudflare's OpenAI Whisper API for high-quality speech-to-text transcription.

Installation

Prerequisites

• Java 11 or higher
• Maven (for dependency management)
• Cloudflare account with access to OpenAI Whisper API
• FFmpeg (for audio extraction)

Setup

1. Clone this repository:

   git clone https://github.com/yourusername/yourproject.git
   cd yourproject

2. Install dependencies:

   mvn install

3. Make sure ffmpeg is installed and available in your system's PATH.
4. Replace placeholders for CF_ACCOUNT_ID and "CF_API_TOKEN" in Util.java with your Cloudflare access.