「audio」の検索結果

Convert various file formats (PDF, Office documents, images, audio, web content, structured data) to Markdown optimized for LLM processing. Use when converting documents to markdown, extracting text from PDFs/Office files, transcribing audio, performing OCR on images, extracting YouTube transcripts, or processing batches of files. Supports 20+ formats including DOCX, XLSX, PPTX, PDF, HTML, EPUB, CSV, JSON, images with OCR, and audio with transcription.

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Use audio-diffusion-pytorch for PyTorch waveform diffusion generators, text-conditioned audio generation, inpainting, upsampling, vocoding, and diffusion autoencoding.

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

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Provider-independent production guidance for translating measured audio features into deterministic video timing and motion. Use for beat-, onset-, phrase-, energy-, silence-, or spectrum-reactive visualizers, edits, typography, and generated compositions; not for music-video concept direction, audio generation, or a runtime-specific recipe.

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Produce audio-first podcast episodes with generative tools — design the show and episode format (interview, narrative, news brief, two-host conversational), write scripts for the ear, decide between fully-synthetic and hybrid (recorded human + synthetic) production and meet the disclosure duty each triggers, cast and direct multi-voice TTS for consistency and chemistry, build episode structure (cold open, intro/outro, segments, ad slots), assemble and edit, clear music and SFX rights, hit podcast loudness and delivery standards, ship metadata/chapters/transcripts through RSS, and pass platform AI-content policy and QA before publishing. Use this skill whenever the deliverable is a podcast episode or a podcast show bible, or when an agent must make production, rights, disclosure, or delivery decisions for spoken-word audio. Not for music tracks, single-voice notification prompts, or video where picture leads (route audio-for-video to a video skill).

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Provider-independent audio mixing and mastering direction for AI agents finishing generated videos, ads, trailers, explainers, podcasts, recuts, avatar clips, music videos, documentaries, and social content. Use when planning, mixing, repairing, mastering, QCing, or delivering dialogue, music, ambience, and sound effects, including loudness/true-peak targets, intelligibility, accessibility, stems, stereo/immersive decisions, platform/client specs, and final audio QA.

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Produce full-length audiobooks and long-form narration with generative voice tools. Use when the task is to turn a manuscript or long text into hours of spoken audio: preparing the manuscript for narration (front/back matter, footnotes, tables, dialogue), casting a single narrator or full cast, controlling pronunciation and voice consistency across a whole book, running a proofing/QC listen, meeting a retailer's technical delivery specs (RMS, peak, noise floor, room tone, chapterized files, metadata), and choosing a distribution route under each platform's current AI-narration policy. Not for short TTS clips, single-line voiceover, podcast production, or captioning existing video.

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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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Use when writing or debugging prompts for MiniMax H3 (Hailuo 3) video-with-audio generation, running the open weights locally in ComfyUI, choosing a quant or an acceleration LoRA for the VRAM you have, wiring reference-to-video with images, video or audio, or when a generated clip produces gibberish speech, drifts off a reference identity, garbles audio after a latent upscale, or refuses to run on a build that looks current.

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See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio, video), and create real time alerts for events from live streams or desktop capture.

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Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

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。

Turn any website into an audio-enabled experience. Covers TTS reading mode (SpeechSynthesis API), pre-recorded MP3 audio player, and Voice CRO trigger system. Zero dependencies, works on any static or dynamic site. Use when adding read-aloud, audio player, or voice-based conversion features.

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Summarizes audio content using AssemblyAI's LeMUR (Large Language Model for Audio Understanding) API. Chains the /v2/transcript endpoint with /lemur/v3/generate/summary for contextual audio intelligence.

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Identifies audio content using Chromaprint/AcoustID fingerprinting, Shazam API recognition, and ACRCloud monitoring. Matches music, speech, and ambient audio against fingerprint databases.

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Burn Red Book audio CDs or MP3 data CDs on macOS via cdrdao, sourcing from Hoodrat HDD or local files. Audio CDs carry CD-Text from ID3 tags; MP3 discs use ISO9660+Joliet (~700 MB). Handles full-album burns and cherry-picked playlists. Triggers on 'burn CD', 'burn album', 'make audio CD', 'mixtape disc', 'soundtrack for the car'.

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Build AI audio transcription systems. TRIGGERS - Use when user needs help with ai-audio-transcriber related 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。

Build AI audio processing pipelines. TRIGGERS - Use when user needs help with ai-audio-processor related 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。

Game audio principles. Sound design, music integration, adaptive audio systems.

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Use when adding multimedia to PyQt/PySide6 apps - audio and video playback with QMediaPlayer, camera capture with QCamera and QMediaCaptureSession, audio/video recording with QMediaRecorder, GStreamer backend setup, or codec and platform compatibility issues

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Reproduce and debug "only happens in a DAW" audio plugin bugs (cutouts, glitches, parameter-change failures) entirely offline — headless Processor scenes for DSP bugs and a standalone AudioUnit host probe for adapter/host-interaction bugs. Use when a plugin misbehaves in Logic/Live/etc. but unit tests are green.

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Guides implementation of custom Wwise or FMOD DSP plugins from scratch — effect, source, and mixer plugin types. Use when the user wants to create a new Wwise plugin, build an FMOD DSP effect, or implement a custom game audio middleware plugin. Trigger on phrases like "create a Wwise effect plugin", "build an FMOD DSP", "implement custom game audio middleware plugin", "how do I write a Wwise source plugin", or "set up an FMOD DSP description".

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Rewrite raw meeting audio transcriptions into clean, accurate meeting minutes in Traditional Chinese. Use when the user has an unprocessed audio transcription file with recognition errors and needs it cleaned up into proper meeting minutes.

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Generate spoken audio from text, single or multi-speaker, including voice notes or messages for chat, audio for artifacts, and audio from cron jobs. For podcasts, briefings, or narrated summaries, use podcast.

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。

Game audio principles. Sound design, music integration, adaptive audio systems.

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。