I've watched presenters read every word from a page, then freeze the moment someone asks a question. I've also watched speakers explain a deck calmly and handle the room with confidence. As a top-university graduate, I also want students to see what a strong presentation script can look like. The difference is usually preparation: find the deck's logic skeleton first, then build the talk track, transitions, and Q&A around it.
YouTube video-to-text tool for students turning lectures into notes, podcast listeners hunting a quote, and anyone tired of scrubbing long videos. Paste any link — tutorials, talks, podcasts, lectures, or interviews — and get a clean verbatim transcript with AI summary and key points, often under two minutes. Output: plain text, timestamped Markdown, or SRT subtitles. Transcripts stay in the source language so quoted lines stay accurate, while summaries auto-translate to your chat language.
Surgically trim awkward pauses, dragging breaths, and robotic TTS dead air in 0.4s. Built for TikTok, Reels, Shorts, and podcasts to boost audience retention by 15%-25%. Features studio-grade 10ms anti-click cosine crossfading and 50ms voice-head safety buffers to guarantee crisp, zero-artifact broadcast audio.
Turn a script into a vertical narrated short with voice and subtitles that light up word by word. Speech recognition recovers the timings from the generated audio, so captions never drift when you change the voice, the speed, or a line.
我長期處理中英夾雜的技術型影音內容（教學影片、會議與簡報錄音），很清楚這類素材最頭痛的就是專有名詞和英文縮寫被聽錯。這個 Skill 把我實際在用的整套做法工具化：以 faster-whisper 在本機 CPU 就能轉錄（免 GPU、免雲端 API、免費），並用「轉錄前餵專有名詞提示＋轉錄後批次修正同音錯字」兩道工序把準確率拉高；YouTube 連結則走「先抓現成字幕、失敗自動改抓音訊轉錄」的穩定路線，最後一併產出 SRT 字幕、逐字稿與帶時間戳的重點摘要。全程本機運算、檔案不上雲，適合在意內容隱私又要快速消化長影音的人。 I work daily with mixed Chinese-English technical audio, where jargon and acronyms get mis-heard most. This Skill packages my workflow: faster-whisper runs locally on CPU (no GPU, no cloud API)
For a short you already posted. Send the video plus a screenshot of its retention graph (or your average % viewed) and get the curve redrawn with the drop-offs marked, the frame on screen at each drop, every leak ranked, a cut list with the new target length, and a verdict printed next to its threshold.
Put in a presentation PDF and get a 1920x1080 lecture video mp4 with narration on every slide, plus a chapter list to paste into the YouTube description and an SRT subtitle file. No API key (only an online edge-tts call), and sentence captions, progress badge and crossfades can be turned on or off. Measured: one 5-slide lecture took 73 s (0.6 s extract + 5 s speech + 67 s video assembly, Apple Silicon). For online courses, internal training and product videos without recording.
**Mac only (Apple Silicon M1–M4) — not available for Windows or Intel Macs yet.** Turn recordings into notes without uploading a single second of audio anywhere. Lectures, meetings, screen recordings — you record them and never turn them into notes, because transcribing is tedious and every cloud transcription service means uploading private audio to someone else's server. This skill sets up a transcription pipeline that runs entirely on your own Mac.