「audio」の検索結果

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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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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音频降噪：去除录音中的背景噪声、电流声、风噪、嗡嗡声，基于 ffmpeg 滤镜链（afftdn/highpass/lowpass）。 当用户说"降噪""去噪""去杂音""消除背景噪声""电流声""风噪""录音有杂音""音频降噪"时使用。 和 audio-editing 的区别：audio-editing 做剪辑/转码/音量等通用音频操作（内置 denoise 兜底），本 SKILL 专做降噪调参。

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音频混合 / 混音：把旁白口播 + 背景音乐 + 音效混成一轨，BGM 自动循环补足并可闪避（旁白说话时自动压低 BGM 保证人声清晰）。当用户说 混音、音频混合、旁白加背景音乐、配音加BGM、人声和音乐混一起、加音效、音频叠加、BGM 压低、闪避、ducking、把配音和bgm合起来 时使用。基于 shared/scripts/audio_mix.py。与 audio-editing concat 区别：concat 是前后顺序拼接，本 SKILL 是同时叠加混音；与 video-editing bgm 区别：那个给视频配乐，本 SKILL 输出纯音频。

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音频可视化视频：把纯音频（播客片段、音乐、口播金句、电台）渲染成带动态波形/频谱的视频，配封面和标题，好发到抖音/B站/视频号等只收视频的平台。当用户说 音频可视化、音频转视频、播客做成视频、音频波形视频、音乐可视化、给音频配画面、声波视频、频谱视频、把音频发到视频平台、电台切片视频 时使用。基于 shared/scripts/audio_viz.py（ffmpeg showwaves/showcqt/showspectrum）。与 audio-mix 区别：那个输出音频，本 SKILL 输出视频；与 slideshow-video 区别：那个用图片，本 SKILL 用音频驱动画面。

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Generate AI-powered podcast-style audio narratives using Azure OpenAI's GPT Realtime Mini model via WebSocket. Use when building text-to-speech features, audio narrative generation, podcast creation from content, or integrating with Azure OpenAI Realtime API for real audio output. Covers full-stack implementation from React frontend to Python FastAPI backend with WebSocket streaming.

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Generate AI videos using ByteDance Seedance models via Volcengine Ark API. Supports text-to-video, image-to-video (first frame, first+last frame), multimodal reference (images+videos+audio), video editing, video extension, web search enhancement, audio generation, draft mode, offline inference, and continuous video chaining. Use when user wants to generate, create, edit, or extend AI videos from text prompts, images, videos, or audio.

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Calculate per-second RMS energy from audio files. Use when you need to analyze audio volume patterns, prepare data for silence/pause detection, or create an energy profile for audio analysis tasks.

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Extract, normalize, mix, and process audio tracks - audio manipulation and analysis

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Detect speech segments in audio using VAD tools like Silero VAD, SpeechBrain VAD, or WebRTC VAD. Use when preprocessing audio for speaker diarization, filtering silence, or segmenting audio into speech chunks. Choose Silero VAD for short segments, SpeechBrain VAD for general purpose, or WebRTC VAD for lightweight applications.

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Combine visual features (face detection, lip movement analysis) with audio features to improve speaker diarization accuracy in video files. Use OpenCV for face detection and lip movement tracking, then fuse visual cues with audio-based speaker embeddings. Essential when processing video files with multiple visible speakers or when audio-only diarization needs visual validation.

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Google Text-to-Speech (gTTS) for converting text to audio. Use when creating audiobooks, podcasts, or speech synthesis from text. Handles long text by chunking at sentence boundaries and concatenating audio segments with pydub.

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Generate production subtitle artifacts from the final narration audio or final merged video using Volcengine Doubao ASR word timestamps. Use for local IndexTTS2 videos, Xiaohei page videos, talking-head delivery subtitles, SRT/VTT export, or whenever subtitle timing must match the final audio. Do not use script-length interpolation for final deliverables.

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Transcribes audio or video to speaker-labeled, timestamped text, locally with MLX on Apple Silicon or remotely. Use for 转录 / 录音转文字 / 说话人分离 / 字幕, and also for preparing audio for ASR without transcribing: 转格式, 降采样到 16kHz, merging recorder segments, or compressing and speeding up audio before 飞书妙记 — even when it looks like a one-line ffmpeg job.

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 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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Assemble an editorial-motion podcast-clip ad from a config — a real clipped podcast MP3 carries the narrative while N flat limited-palette editorial-illustration keyframes (one look pack) are animated NOT by generative i2v but by DETERMINISTIC ffmpeg ken-burns (zoompan) + hard cuts (no crossfades, which expose geometric drift), each beat snapped to its spoken line, the real audio muxed, Whisper-driven captions burned only mid-sentence, and closed on a PIL brand end card — never AI-rendered text. This is the FREE deterministic assembly stage (ffmpeg ken-burns + hard concat + audio mux + captions + end card); the real audio is clipped from source and the keyframes come from create-image-fal. Use for the editorial-motion-podcast format.

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Runs LiveKit agent simulations and acts on the results. Use when the user says "run my simulations", "regression test my agent before deploying", "run the scenarios", "use lk agent simulate", "did my agent pass", "why did this scenario fail", "run simulations in CI", "test the audio pipeline", "check turn-taking and interruptions", or wants to check whole-conversation behavior before shipping. Covers text and audio mode and what each catches, running against a local or deployed agent, degraded-audio flags, automating a pre-release run, and triaging failures with list, view and export. For writing the scenarios use writing-livekit-scenarios. Not the default for a bare "test my agent", which goes to debugging-livekit-agents. Use this skill when the user names simulations, scenarios, a run, CI, or shipping.

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Extract features from 1D signals using signalTimeFeatureExtractor, signalFrequencyFeatureExtractor, and signalTimeFrequencyFeatureExtractor. Use when computing time-domain features (amplitude, energy, shape factors), frequency-domain features (spectral location, power, bandwidth, PSD), or time-frequency features (spectral shape, instantaneous, ridges, wavelet, EMD-derived) on a per-frame basis. Use when the user asks to "extract features", "compute spectral features", "build a feature table for a classifier", "get per-frame statistics", "run feature extraction on this signal", or describes a vibration / biosignal / radar / sensor signal needing features for downstream ML or analysis. Includes optional GPU acceleration via canUseGPU and gpuArray. Does not cover filter design, audio-specific feature extraction (use audioFeatureExtractor in Audio Toolbox instead), batch dataset orchestration, or 2D / image features.

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Expert blueprint for rhythm games including audio synchronization (BPM conductor, latency compensation with AudioServer.get_time_since_last_mix), note highways (scroll speed, timing windows), judgment systems (Perfect/Great/Good/Bad/Miss), scoring with combo multipliers, input processing (lane-based, hold note detection), and chart/beatmap loading. Based on DDR/osu!/Beat Saber research. Trigger keywords: rhythm_game, audio_sync, timing_judgment, note_highway, combo_system, BPM_conductor, latency_compensation.

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Edit podcast audio or video — trim pre/post-show chat, remove filler words, cut silences, enhance audio quality, and cut a video version of the same edit. Use when the user asks to edit a podcast, clean up audio, remove fillers, trim a recording, or improve voice quality.

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Dung khi mot CA NHAN can AM THANH bang AI — clone giong noi, lam podcast, audiobook, voiceover cho video: 3 use case gom voiceover ngan cho TikTok va Reels, podcast 30-60 phut, audiobook; quy trinh thu mau giong, chinh cam xuc va toc do, cong bo dung luat, tai su dung 1 podcast thanh 10 clip ngan. Kich hoat khi user nhac 'voice clone', 'clone giong noi', 'ElevenLabs', 'lam podcast', 'audio AI', 'voiceover AI', 'ngai thu am moi ngay', 'cat podcast ra clip ngan'. Khong dung cho — video co hinh anh nguoi hoac avatar thi dung skill 24-ai-avatar-production; viet loi thoai va hook noi thi dung skill 04-script-video; viet bai dai dang chu thi dung skill 26-thought-leadership-content.

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Use when a PERSONAL brand needs AUDIO — voice cloning with ElevenLabs, Murf, or PlayHT, podcast production, audiobooks, and voiceover: short voiceover for TikTok and Reels, a 30 to 60 minute podcast format, and a 1-to-10 repurpose turning one episode into ten clips, in English with US, UK, AU, and SG accents. Trigger on 'voice clone', 'ElevenLabs', 'start a podcast', 'audiobook narration', 'AI voiceover for my videos', 'I hate re-recording the same intro'. Not for — video with a talking-head avatar, see `24-ai-avatar-production-global`; the script being read aloud, see `04-script-video-global`; written long-form posts, see `26-thought-leadership-content-global`.

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Volcano Engine AI MediaKit talking-head video editing Skill: a one-stop workflow from environment setup through media management, audio processing, talking-head cuts, video export, review UI, and iterative refinement. You MUST invoke this Skill when the user mentions talking-head editing, cutting talking video, video editing, removing pauses, processing audio, exporting talking video, automatic editing, removing verbal slips, or similar. Also invoke when the user uploads video or audio and asks for editing.

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Create AI avatar and talking head videos via inference.sh CLI. Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS). Also: OmniHuman, Fabric, PixVerse. Audio: Inworld TTS-2 (100+ languages, emotion steering for characters), ElevenLabs, Kokoro. Capabilities: audio-driven avatars, text-to-avatar, lipsync videos, talking head generation, virtual presenters, UGC content. Use for: AI presenters, explainer videos, virtual influencers, dubbing, marketing videos, UGC ads, gaming avatars, NPC dialogue. Triggers: ai avatar, talking head, lipsync, avatar video, virtual presenter, ai spokesperson, audio driven video, heygen alternative, synthesia alternative, talking avatar, lip sync, video avatar, ai presenter, digital human, ugc, ugc video, ugc ad, avatar ugc

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。