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WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)

Scene-aware storyboard for DeepSeek Harness: 9-16 numbered cells with timestamps + transcript + an audio envelope, packed into ONE image (384 tokens). Two tools: video_storyboard and video_zoom.

:clock8: The original jQuery plugin that makes it easy to support automatically updating fuzzy timestamps (e.g. "4 minutes ago").

Dockerfile for WhisperX: Automatic Speech Recognition with Word-Level Timestamps and Speaker Diarization (Dockerfile, CI image build and test)

Verbatim Automatic Speech Recognition with improved word-level timestamps and filler detection

HeadTTS: Free neural text-to-speech (Kokoro) with timestamps and visemes for lip-sync. Runs in-browser (WebGPU/WASM) or on local Node.js WebSocket/REST server (WebGPU/CPU).

A speech-to-text system you can train for $25. A frozen speech encoder and a Qwen LLM joined by a small trained projector, with word timestamps, speaker diarization, a batched HTTP server, a live demo, and a free course.

Portable AI-agent skill: turn YouTube, Instagram, TikTok, X and other video links into Obsidian-ready Markdown notes: captions or local Whisper transcripts, frames, metadata and timestamps

MOSS-Transcribe-Diarize 0.9B is an open-source SOTA end-to-end audio understanding model for long-form multi-speaker transcription, diarization, timestamps, and acoustic event awareness.