925 件 ・ 関連度順
概要と使いどころ
Use when the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (`scripts/text_to_speech.py`) with built-in voices and require `OPENAI_API_KEY` for live calls. Custom voice creation is out of scope.
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。
Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio/video, extract text from recordings, or label speakers in interviews or meetings.
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。
OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.
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。
Add data-driven audio with correct prediction, audience, resources, attribution, and verification.
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。
Theatre.js アニメーションツールキットリファレンス。 @theatre/core / @theatre/studio / @theatre/r3f / @theatre/dataverse。 getProject, Sheet, Sequence, Object, val, onChange, prop-types（number / rgba / compound / image）。 studio initialize / extend / transaction / scrub / createPane。 SheetProvider, editable, useCurrentSheet, useVal, usePrism, useAtom。 keyframe アニメーション、audio sync、state JSON、React Three Fiber 統合。
Windows アプリ開発 (DirectX / WinRT メディア) のグラフィックス・メディア API リファレンス。 Direct2D (ID2D1Factory, ID2D1DeviceContext, ID2D1Bitmap1, ID2D1Effect, ID2D1PathGeometry), DirectWrite (IDWriteFactory, IDWriteTextLayout, DWriteCore), Direct3D 11/12 (D3D11CreateDevice, DXGI SwapChain, HLSL, D3D12 PipelineState), Microsoft.UI.Composition (Compositor, Visual, ExpressionAnimation, InteractionTracker, MicaController), カメラ・画面キャプチャ (MediaCapture, MediaFrameReader, GraphicsCaptureSession, Windows Studio Effects)、音声・動画再生 (MediaPlayer, MediaPlaybackSession, AudioGraph, MediaTranscoder, AdaptiveMediaSource)。
Apple オンデバイス機械学習フレームワークリファレンス。 Core ML / Create ML / Vision / Natural Language / Speech。 MLModel, MLModelConfiguration, MLMultiArray, MLComputeUnits, MLImageClassifier, MLTextClassifier, MLDataTable, VNImageRequestHandler, VNRecognizeTextRequest, VNCoreMLRequest, NLTagger, NLLanguageRecognizer, NLEmbedding, SFSpeechRecognizer, SFSpeechAudioBufferRecognitionRequest, SFTranscription。
Azure Speech to Text REST API for short audio (Python). Use for simple speech recognition of audio files up to 60 seconds without the Speech SDK.
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。
Single-track / single-episode music-player mockup template — glassmorphic iOS-Music style player card with ambient album-art wash, for showcasing one song, one podcast episode, or one audio jingle as a shareable interactive surface.
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。
Azure Speech to Text REST API for short audio (Python). Use for simple speech recognition of audio files up to 60 seconds without the Speech SDK.
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。
Download audio recordings from Coval voice simulations. Use when user wants to listen to or analyze call recordings.
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。
Azure Speech to Text REST API for short audio (Python). Use for simple speech recognition of audio files up to 60 seconds without the Speech SDK.
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。
AI music generation with ACE-Step 1.5 — background music, vocal tracks, covers, stem extraction, audio repainting, and continuation for video production. Use when generating music, soundtracks, jingles, or working with audio stems. Triggers include background music, soundtrack, jingle, music generation, stem extraction, cover, style transfer, repaint, continuation, or musical composition tasks.
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。
Process multimedia files with FFmpeg (video/audio encoding, conversion, streaming, filtering, hardware acceleration), ImageMagick (image manipulation, format conversion, batch processing, effects, composition), and RMBG (AI-powered background removal). Use when converting media formats, encoding videos with specific codecs (H.264, H.265, VP9), resizing/cropping images, removing backgrounds from images, extracting audio from video, applying filters and effects, optimizing file sizes, creating streaming manifests (HLS/DASH), generating thumbnails, batch processing images, creating composite images, or implementing media processing pipelines. Supports 100+ formats, hardware acceleration (NVENC, QSV), and complex filtergraphs.
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。
Build with OpenAI's stateless APIs - Chat Completions (GPT-5, GPT-4o), Embeddings, Images (DALL-E 3), Audio (Whisper + TTS), and Moderation. Includes Node.js SDK and fetch-based approaches for Cloudflare Workers. Use when: implementing chat completions with GPT-5/GPT-4o, streaming responses with SSE, using function calling/tools, creating structured outputs with JSON schemas, generating embeddings for RAG (text-embedding-3-small/large), generating images with DALL-E 3, editing images with GPT-Image-1, transcribing audio with Whisper, synthesizing speech with TTS (11 voices), moderating content (11 safety categories), or troubleshooting rate limits (429), invalid API keys (401), function calling failures, streaming parse errors, embeddings dimension mismatches, or token limit exceeded.
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。
Research synthesis from sources — "summarize these URLs or papers", "research this topic with these sources", "create a podcast about", "audio overview", "mind map", "quiz from these sources", "flashcards", "deep research on". Wraps Google NotebookLM via notebooklm-py.
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。
OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.
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。
Create HTML-based video compositions, animated title cards, social overlays, captioned talking-head videos, audio-reactive visuals, and shader transitions using HyperFrames. HTML is the source of truth for video. Use when the user wants a rendered MP4/WebM from an HTML composition, wants to animate text/logos/charts over media, needs captions synced to audio, wants TTS narration, or wants to convert a website into a video.
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。
Audio spectrograms/features (mel, chroma, MFCC) via CLI.
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。
Comprehensive video/audio processing with FFmpeg. Use for: (1) Video transcoding and format conversion, (2) Cutting and merging clips, (3) Audio extraction and manipulation, (4) Thumbnail and GIF generation, (5) Resolution scaling and quality adjustment, (6) Adding subtitles or watermarks, (7) Speed adjustment (slow/fast motion), (8) Color correction and filters.
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。
Text-to-speech conversion using node-edge-tts npm package for generating audio from text. Supports multiple voices, languages, speed adjustment, pitch control, and subtitle generation. Use when: (1) User requests audio/voice output with the "tts" trigger or keyword. (2) Content needs to be spoken rather than read (multitasking, accessibility, driving, cooking). (3) User wants a specific voice, speed, pitch, or format for TTS output.
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。
Requires OFOX_API_KEY — create one at https://app.ofox.ai, plus the music file the finished video must carry. Your audio never reaches the API (measured) — the visuals are written to the track's tempo, mood and sections, then your own file is laid on locally at zero cost. One job caps at 30 seconds, so a three-minute song is six jobs minimum and the cost table says that before anything is spent. Use when a user has a specific piece of music and wants visuals for it, e.g. "make a music video for this track", "visuals for my song", "an MV for this instrumental", "generate footage cut to this beat". Do not use for cheap vertical social drafts (shorts-reels), a brand film that happens to have a music bed (seedance-ad-creative), or when there is no particular audio file the finished video has to carry.
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。
Build, debug, optimize, and deploy ComfyUI workflows for diffusion image, video, and audio generation. Activate on: ComfyUI workflow, ComfyUI custom node, ComfyUI API, ComfyUI Manager, KSampler, FLUX in ComfyUI, Wan 2.2 ComfyUI, Hunyuan video ComfyUI, LTX video ComfyUI, IPAdapter, ControlNet ComfyUI, Kijai wrapper, ComfyDeploy, RunComfy, ComfyUI security, GGUF quantization, TeaCache, Nunchaku, ACE-Step ComfyUI, F5-TTS ComfyUI, subgraphs ComfyUI. NOT for: A1111/Forge/Invoke (different UIs), training pipelines from scratch, non-diffusion ML models, or general image-API integrations (use generative-video-2026 / generative-music-audio / media-gen-deployment).
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。
撮影済みの動画や画面収録から見どころを選び、カット・構成整理・字幕や音声の追加を進めます。長い録画の短編化からSNS向けの画角調整、編集ソフトでの仕上げまで扱うスキルです。