sbin

Introduction​

• A Brief Introduction to the Ad Insertion Optimization Service
• A Brief Introduction to the Batch Automation Service
  • “When a new episode is uploaded → Subtitles → Analysis → Automatic indexing → Automatic generation of character highlight clips and episode summaries → Upload to S3” Set a single rule, and it handles bulk processing automatically

Introduction​

Schema Repository → https://github.com/SceneMakerAI/sm_db

https://programs.sbs.co.kr/sports/ag2026/clips/90399

Introduction​

The technical objectives of this project are twofold: processing performance and scene analysis accuracy. We measured what we could currently verify using processing logs from 10 episodes of the SBS drama “Manager Kim.” According to the logs, processing performance is within the target range, while accuracy has not yet been measured.

Introduction​

This post documents the process of identifying, fixing, and submitting fixes for issues in the open-source software I used while developing SceneMaker. I’ve outlined where I found opportunities to contribute, the order in which I submitted my changes, and which ones were accepted.

Introduction​

Posting the results of testing on the actual UI and the time taken

Introduction​

MODEL_QWEN3_ASR = MODEL_ROOT / "Qwen3-ASR-1.7B"
MODEL_QWEN3_ALIGNER = MODEL_ROOT / "Qwen3-ForcedAligner-0.6B"

Introduction​

Start by writing the four requests for the assignment

Introduction​

Include GitHub discussions, GitHub commits, etc.

Introduction​

Watch the PowerPoint Presentation, Then Take Notes