「whisper」の検索結果

Batch Whisper transcription of video or audio (WAV, podcasts) with a re-runnable provenance record. Use to transcribe recordings.

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Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration

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Transcribe audio and video from URLs (YouTube, direct media links) using WhisperKit locally. Optionally analyze transcripts with AI when explicitly requested. Use when users provide URLs to media content and request transcription or speech-to-text conversion.

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Earnings sentiment analysis, analyst estimates vs guidance, earnings surprise history, consensus sentiment, earnings revision trends, analyst rating changes, earnings beat miss track record, guidance accuracy, whisper numbers, pre-announcement sentiment

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Patterns for building multimodal AI applications that combine text, images, audio, and video. Covers vision APIs, audio transcription, and unified pipelines. Use when "multimodal AI, vision API, image understanding, GPT-4V, Claude vision, audio transcription, Whisper, document extraction, image to text, " mentioned.

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Azure OpenAI is Microsoft's hosted service for OpenAI models (GPT, gpt-image, Whisper, embeddings) on Azure infrastructure. Use when calling OpenAI models through Azure, authenticating with Managed Identity or Entra ID, setting up content filters, or deploying with enterprise compliance, regional data residency or private networking.

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Watch a video from YouTube, Instagram, X/Twitter, Vimeo, TikTok or any of ~1800 yt-dlp sites (or a local path). Downloads with yt-dlp, extracts auto-scaled frames with ffmpeg, pulls the transcript from captions (or local mlx-whisper fallback, no API key), and hands the result to Claude so it can answer questions about what's in the video.

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Use when the user has audio or video and wants a timestamped transcript (SRT) in the source language. Routes by source language — Chinese defaults to Volcano (豆包) ASR; other languages (Spanish, English, Portuguese, French, Italian, Japanese, Korean, etc.) use OpenAI Whisper API with word-level timestamps and self-assembled cues. Outputs SRT with punctuation-bounded cues capped for on-screen reading. Triggers — "转写", "转成字幕", "做 SRT", "transcribe", "make subtitles", "speech to text", "出字幕".

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视频文案分析一站式工具。下载在线视频（B站/YouTube/抖音等）、使用FunASR Nano进行中文语音转录、 自动校正文稿、并进行三维度综合分析（TextContent/Viral/Brainstorming）。 使用场景：当用户需要分析短视频文案、提取视频内容、学习爆款文案技巧时。 关键词：视频分析、文案分析、语音转文字、FunASR、Whisper、爆款分析、视频下载

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飞书妙记：妙记相关基本功能。1.查询妙记列表（按关键词/所有者/参与者/时间范围）；2.获取妙记基础信息（标题、封面、时长 等）；3.下载妙记音视频文件；4.获取妙记相关 AI 产物（总结、待办、章节）；5.上传音视频生成妙记，也支持将本地音视频文件转成纪要、逐字稿、文字稿、撰写文字等产物。遇到这类请求时，应优先使用本 skill，而不是尝试 `ffmpeg`、`whisper` 等本地转写命令。飞书妙记 URL 格式: http(s)://<host>/minutes/<minute-token>

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Expert guide for AI image generation (Flux, DALL-E, Stable Diffusion), video generation (Sora, Runway), voice synthesis (ElevenLabs TTS), and speech recognition (Whisper STT) integration / Panduan ahli integrasi AI generasi gambar, video, suara (TTS), dan pengenalan suara (STT).

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Transcribe audio/video files via MLX Whisper (Apple Silicon). Usage: /transcribe path/to/file.mp3

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Build and query a local Markdown knowledge base ("vault"). TWO functions — (1) CONVERT raw files (PDF, Word/docx, PowerPoint/pptx, Excel/xlsx, csv/tsv, images, html, md/txt, json/yaml/code, audio/video) into clean Markdown with retrieval-friendly frontmatter; local-first (pandoc / python-pptx / openpyxl / pymupdf4llm / whisper), with cloud OCR (MinerU) only as a fallback. (2) ANSWER questions over the resulting vault with retrieval discipline — self-monitor coverage, flag missing/lossy content, and propose Maps-of-Content (MOCs). Triggers: "build/sync my local knowledge base", "convert these files to markdown for AI", "整理我的资料库", "把文件转成 md 给 AI 读", "本地知识库", "读我的本地 vault 回答", "这个主题我的资料里怎么说". Not for: one-off web research, or files that are already in a single doc you can read directly.

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素材改编专家（艾达 · Ada）。擅长视频内容分析（YT-VITA）、精彩片段提取、视频翻译（AI声纹克隆+唇型同步）、多媒体合成、跨语言本地化、本地视频预处理（ffmpeg+whisper）。 触发词："分析这段视频的内容"、"从长视频中提取精彩片段"、"把这段中文视频翻译成英文"、"把这些图片和视频合成一段宣传片"、"把这个视频的对话转成文字"。

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Speech-to-text transcription and translation via OpenAI Audio API -- models, response formats, timestamps, prompting, streaming, chunking, and diarization

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Burn timed, styled captions into a finished video on the local machine, without re-rendering the source. This is the manual fallback to the API's captioning endpoint, POST /v1/captions, which stays the default path: come here when the style the user wants is outside the API's presets, when the wording has to be hand-corrected before it is burned into the pixels, or when the source was rendered with audio disabled and the API refuses it. Transcribes the audio with Whisper, groups words into reading phrases, renders the captions in a real browser via HyperFrames, and composites them over the source with ffmpeg using a real alpha channel. Use when the user has an MP4 with speech and asks to add captions, subtitles, burned-in text, TikTok-style captions or word-by-word text to it, and the API path has been ruled out. Runs out of band, so it costs no credits and works on any video file whoever generated it. Not for generating video (use the video skills) and not for a separate .srt/.vtt sidecar file.

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Builds a hand-sculpted stop-motion CLAY ad on the Novoads REST API as a STORYBOARD: five to eight beats, each rendered from its own key frame, a storyteller narration laid into the gaps, a music bed, captions burned on, assembled locally with ffmpeg. Carries the genre's arc (named protagonist, inciting moment, social beat, quiet despair, sculpted clay infographic, discovery, transformation, resolution card), and also recreates a found clay ad by reading the reference video locally with ffmpeg and Whisper. Use for ANY clay or stop-motion ask at ANY length: "claymation ad", "stop-motion ad", "clay ad", "a quick clay ad", "plasticine characters", "make an ad like this clay one", or a reference video with sculpted clay characters in it. There is no one-call tier here, so ffmpeg is required. Not for the smooth 3D animated look (use pixar-ad, which covers every Pixar-style length), talking-head UGC (novoads-api), or a static image ad.

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Generate TikTok/Shorts-style karaoke captions using MLX Whisper, ASS subtitles, and FFmpeg libass. Use when burning word-level highlight captions into a video, matching caption style from a screenshot, rendering ASS karaoke subtitles, or when the user runs /karaoke-captions.

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Audio file → full publishing kit pipeline. From a single .mp3 or .wav per episode, generates Whisper-large-v3 transcript with word-level timestamps, automatic chapter detection (audio scene change + topic shift), two show-notes lengths (scannable summary + long-form SEO).

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Extracts timed subtitles from local video/audio files using Whisper. Outputs SRT format with accurate timestamps. Handles complex filenames automatically. Use when user asks to "extract subtitles", "get subtitles", "transcribe video", "识别字幕", "提取字幕", or "获取字幕".

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Add voice message transcription to NanoClaw using OpenAI's Whisper API. Automatically transcribes WhatsApp voice notes so the agent can read and respond to them.

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Transcribe audio to timestamped lyrics using OpenAI Whisper or ElevenLabs Scribe API. Outputs LRC, SRT, or JSON with word-level timestamps. Use when users want to transcribe songs, generate LRC files, or extract lyrics with timestamps from audio.

日本語の概要は準備中です。原文の説明を表示しています。

Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration

日本語の概要は準備中です。原文の説明を表示しています。

FREE voice recognition using Groq's complimentary Whisper API.

日本語の概要は準備中です。原文の説明を表示しています。