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Transcribe audio/video to text with word-level timestamps using OpenAI Whisper. Use when you need speech-to-text with accurate timing information for each word.

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Transcribe audio segments to text using Whisper models. Use larger models (small, base, medium, large-v3) for better accuracy, or faster-whisper for optimized performance. Always align transcription timestamps with diarization segments for accurate speaker-labeled subtitles.

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Process filler word annotations to generate video edit lists. Use when working with timestamp annotations for removing speech disfluencies (um, uh, like, you know) from audio/video content.

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演讲与分享教练。基于Patrick Winston（MIT AI教授）的How to Speak方法论，帮助准备线下培训、技术分享、B站教程视频等演讲场景。当用户提到"演讲"、"分享"、"培训"、"讲课"、"PPT演讲"、"开场"、"结尾"、"如何讲"、"演讲结构"时使用此技能。

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Dialogue writing and revision for screen and stage (对白/台词/潜台词) — merged from Robert McKee's Dialogue (dialogue as action, said/unsaid/unsayable, exposition as ammunition, beat = action/reaction gerunds, flaws of credibility/language/content/design, character-specific vocabulary and grammar, seven scene analyses), Richard Walter (economy, subtext, argument, no small talk, no parentheticals, silence), Neill Hicks (listening, on-the-nose exceptions, energy, five-step exercise), Lu Jun (语言要美; 典雅美/通俗美, 对话三要求 动作性/性格化/潜台词), Lajos Egri (dialogue born of three-dimensional character, escalation), Blake Snyder (cover-the-names test), and screwball-comedy dialogue conventions. Use when writing or polishing dialogue, fixing on-the-nose or expository lines, giving each character a distinct voice, converting a two-hander into a trialogue, writing comedy exchanges, or cutting speeches. Chinese-opera lyrics (戏曲唱词) are in sw-chinese-opera-banqiang, not here.

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Corrects ASR/STT transcription errors — homophones, garbled terms, person-name errors, mixed Chinese/English — with dictionary rules plus Claude's built-in AI, no external API key required. Use to clean meeting notes, lecture transcripts, interviews or speech-recognition text, even when the user only says "fix this transcript". Not for structuring a clean transcript into minutes (use meeting-minutes-taker).

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Generates Chinese/Japanese speech with StepFun's Contextual TTS — default stepaudio-2.5-tts, stepaudio-3-tts for whisper/inline-() prosody. Replaces step-tts-2's voice_label with natural-language instruction. Use for emotional/prosody-controlled synthesis, batch voice lines, migrating from step-tts-2, or cloned voices (2.5/step-tts-2, not v3). Triggers on 阶跃 TTS, 语音合成, 配音. Not for transcription (use stepfun-asr).

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Use when asked 帮我写家长会发言稿, 家长会PPT大纲, 班主任家长会讲话, 期中家长会, 新生家长会, 毕业班家长会, or prepare a parent meeting as a Chinese teacher. Produces a parent-meeting pack in Chinese: an agenda, a timed speech for the 班主任 or subject teacher with class data presented without ranking individual students, a slide outline, specific requests to parents, a one-page handout, answers to likely questions, and a follow-up message for the parents' WeChat group.

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Create video compositions, animations, title cards, overlays, captions, voiceovers, audio-reactive visuals, and scene transitions in HyperFrames HTML. Use when asked to build any HTML-based video content, add captions or subtitles synced to audio, generate text-to-speech narration, create audio-reactive animation (beat sync, glow, pulse driven by music), add animated text highlighting (marker sweeps, hand-drawn circles, burst lines, scribble, sketchout), or add transitions between scenes (crossfades, wipes, reveals, shader transitions). Covers composition authoring, timing, media, and the full video production workflow. For CLI commands (init, lint, preview, render, transcribe, tts) see the hyperframes-cli skill.

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Generate speech or transcribe audio locally with Voicebox. Use for narration, voice assets, dictation, and meeting transcription.

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Use when building or auditing the related-work section of an ACM MM (ACM Multimedia) paper — covering the multimedia literature spread across vision, audio/speech, language, HCI/QoE, and systems, handling arXiv-speed concurrency, keeping citations double-blind, and verifying that cited "ACM MM papers" are ACM MM and not ICMR, MMSys, CVPR, or TOMM.

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Mandatory pre-publish review gate for a UGC video render. Transcribes the finished render's AUDIO with Whisper and word-diffs it against the approved spoken script, then gates pinning the final render (video_project_upsert patch.final_render_id) — blocking a render whose generated audio mis-voices a word (e.g. the approved "human-vetted" spoken as "human witted"), says a different number or brand name, flips a negation, drops an approved phrase, or comes back silent. Correct speech written differently ("5mg" said "five milligrams", "30%" said "thirty percent", a spoken URL, "don't" said "do not", "braxleybands" said "braxley bands", a confirmed pronunciation like "AG1" said "A G one") passes. Runnable, gating counterpart to content-goose's review-transcript-integrity atom. Every ugc-video-formats recipe runs this after render and BEFORE pinning the final render.

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Generate a voiceover (VO) clip via ElevenLabs text-to-speech, ROUTED THROUGH THE elevenlabs-proxy so it bills the Ads agent. Voice id + script text come from the template recipe. Use for the spoken narration of VO-driven video-ad formats (cgi-app-sizzle, flat-vector-explainer, hypermotion). Never call ElevenLabs directly — the proxy attribution is required.

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Access research-grade sensor data using SensorKit for approved studies. Use when an app needs SensorKit entitlement setup, Research Sensor & Usage Data authorization, ambient light, recorded motion, device usage, keyboard metrics, visits, speech, face, wrist temperature, ECG, PPG, acoustic settings, or sleep-session data. Route ordinary motion to CoreMotion and health records/workouts to HealthKit.

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Tokenize, tag, and analyze natural language text using Apple's NaturalLanguage framework and translate between languages with the Translation framework. Use when adding language identification, sentiment analysis, named entity recognition, part-of-speech tagging, text embeddings, or in-app translation to iOS/macOS/visionOS apps.

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Write copy following Sentry brand guidelines. Use when writing UI text, error messages, empty states, onboarding flows, 404 pages, documentation, marketing copy, or any user-facing content. Covers both Plain Speech (default) and Sentry Voice tones.

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Analyze images, video, speech, motion, products, and websites; route local vision, audio, depth, tracking, matting, identity, and restoration models; auto-edit, replicate, enhance, caption, voice, assemble, annotate, validate, and export editable Timeline Studio projects and videos. Use for reference-video remakes, filter and repeated-shot reconstruction, subject-aware reframing, clip splitting, source-time speed curves, Color Wheels grading, ramps and holds, person or product cutout, person or object outline, authorized face swap, shot and timing reconstruction, timeline markers, chapters, beat cues, review notes and ranges, supplied or web-sourced footage, AI video platform selection, cleanup, highlights, product promotion, website walkthroughs, image-to-video assisted edits, optical-flow editing, depth-assisted relighting, grayscale depth-video conversion, depth/2.5D/transition finishing, AI voiceover, subtitles, short-form production, .timeline automation, or editor evaluation.

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Use when the user asks about audio in Higgsfield videos, needs to add dialogue or lip-sync, wants sound effects or ambient sound in generated video, asks about music or BGM in output, or is using any audio-capable model (Kling 3.0, Seedance 1.5 Pro, Seedance 2.0, Veo 3/3.1, Grok Video / Grok Imagine). Also use when the user's prompt would benefit from audio direction but they haven't mentioned it. Also use when the user wants standalone audio — a soundtrack, ambience bed, multi-speaker scene audio (Seed Audio 1.0), or text-to-speech voiceover. Also use to swap or revoice the speaker in an existing video (voice_change), or to clone / create a reusable voice (create_voice → a voice_type 'element' voice usable in TTS and voice change).

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文本转语音工具 - 默认 MiniMax TTS，支持切换 Edge TTS 和 Kokoro TTS (v1.1-zh)

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把带时间戳的 narration.json 合成为中文解说音频。使用 MiMo TTS（mimo-v2.5-tts）或 Fish Audio（s2.1-pro-free）或显式配置的通用 IndexTTS HTTP 服务逐段生成语音， 按时间窗动态适配语速并处理响度；输入输出时间线上的旁白，产出 tts_segments 与 tts_meta.json。 外发说明：每段旁白文字会发给所选 TTS 服务（MiMo / Fish Audio / 用户自托管的 IndexTTS），--voice-ref 的参考音频会发给 MiMo。 另含实验性的英译中 dub 路径：只在显式选择 dub 模式并传 --confirm-voice-rights 时运行，会把源视频音频发到 MiMo ASR， 并以原说话人的声音为参考经 MiMo voiceclone 克隆配音；只可用于用户有权使用、且说话人同意被克隆声音的内容。 触发词：配音、语音合成、TTS、解说配音、 voiceover、text to speech、旁白配音。

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Volcengine VOD audio and video processing tools skill. Use when users need VOD-based media processing or editing: upload local/URL media, stitch videos, trim clips, flip frames, change playback speed, create image-to-video, compose audio/video, extract audio, mix audio, separate vocals/accompaniment, denoise audio, enhance quality, AI super-resolution, frame interpolation, ASR speech-to-text, OCR text extraction, subtitle removal, subtitle embedding, scene slicing, portrait/green-screen matting, highlight extraction, comic style transfer, video translation, drama recap narration, drama script restoration, media info lookup, or playback URL retrieval. The skill submits async VOD jobs, polls task status, and returns generated output links. Not for pure text generation, real-time streaming, or source-free generative video creation.

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Converts audio objects stored in Volcengine TOS into PCM-oriented WAV output through TOS data-process async jobs. Use this skill when the user needs to convert audio to PCM or WAV, resample audio to 16k, convert to mono, change sample format, normalize audio for ASR pipelines, or prepare TOS audio files for speech recognition — even if they don't explicitly mention 'PCM' or 'audio conversion'.

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将文本合成为语音（TTS）。使用火山引擎豆包语音合成 API，支持流式合成、多种音色、语速/音调/音量调节、Markdown 过滤和 LaTeX 公式播报。当用户需要把文字转成语音、生成朗读音频、配音、旁白、播报，或提到「文字转语音」「TTS」「语音合成」「朗读」「配音」时使用本技能。

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Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.

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