Results for “audio-isolation”

Design game audio systems including music, sound effects, ambient soundscapes, adaptive audio, and audio implementation strategy. Use when planning the sonic identity of a game. Also trigger for "game music", "sound effects", "game audio", "soundtrack", "SFX design", "ambient sound", or "adaptive music".

Batch Signal Isolation with Recipe-Driven Processing

Multi-project signal isolation with cascading recipe resolution

Record, search, and analyze music and audio sessions with playback tracking. Use when logging audio sessions, searching metadata, analyzing listening data.

Analyze a screen recording of a manual process and produce targeted, working automation scripts. Extracts frames and audio narration from video files, reconstructs the step-by-step workflow, and proposes automation at multiple complexity levels using tools already installed on the user machine.

Reference for MATLAB audiostreamer (Audio Toolbox R2025a+). Without this skill, agents consistently default to legacy audioDeviceWriter/audioDeviceReader or base MATLAB sound(), producing less capable code. Use when writing code for audio playback, recording, full-duplex device I/O, real-time audio measurements, or audio I/O processing with callbacks. Also use when debugging audiostreamer errors, dropouts, or latency issues, or migrating from audioDeviceReader, audioDeviceWriter, audioPlayerRecorder, or audioplayer/audiorecorder.

Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.

Batch signal isolation for Phenocycler spleen channels using matched blank pairs and kintsugi.signal

Process audio files with SoX (Sound eXchange). Use when a user asks to apply audio effects, mix and combine audio tracks, convert audio formats, batch process audio files, normalize volume, trim silence, add reverb or echo, change tempo or pitch, split audio files, create spectrograms, generate test tones, resample audio, or build audio processing pipelines. Covers all SoX effects, format conversion, mixing, and batch workflows.

Audio spectrograms/features (mel, chroma, MFCC) via CLI.

Control Sonos speakers (discover/status/play/volume/group).

Work with AudioSource, VideoPlayer, audio quiz playback, AI voice, and media streaming in QuizVerse.

Apply the Von Restorff Effect to make the most important element visually distinct from its surroundings, improving attention and recall.

Acoustics Based Design Skill

Control Sonos speakers (discover/status/play/volume/group).

PyTorch library for audio generation including text-to-music (MusicGen) and text-to-sound (AudioGen). Use when you need to generate music from text descriptions, create sound effects, or perform melody-conditioned music generation.

PyTorch library for audio generation including text-to-music (MusicGen) and text-to-sound (AudioGen). Use when you need to generate music from text descriptions, create sound effects, or perform melody-conditioned music generation.

Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.

Audio spectrograms/features (mel, chroma, MFCC) via CLI.

Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.

Create realistic multi-speaker dialogue audio using Dia TTS via the inference.sh CLI, with control over speaker tags, emotion, pacing, and conversation structure.

Audits code quality against a shared contract, producing structured findings and blocking pipeline phases on critical issues without modifying code.

Audio spectrograms/features (mel, chroma, MFCC) via CLI.

AI music generation with ACE-Step 1.5 — background music, vocal tracks, covers, stem extraction 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, or musical composition tasks.

Design and implement real-time audio processing chains using Audio Toolbox streaming objects. Use when building frame-based audio processing loops, multiband filters, dynamic range control, parametric EQ, level metering, loudness metering, SPL metering, octave-band analysis, sample rate conversion, frequency-domain filtering (long impulse responses, custom filter banks), or audio chains in Simulink. Covers visualization (visualize method), interactive tuning (parameterTuner), MIDI control, and Audio Toolbox Simulink blocks. Use when the user says "real-time audio", "streaming audio", "audio filter", "compressor", "equalizer", "level meter", "loudness meter", "SPL meter", "octave bands", "crossover filter", "audio chain", "MIDI control", "convolution reverb", "impulse response streaming", "frequency-domain filter", or asks to process audio frame-by-frame.

PyTorch library for audio generation including text-to-music (MusicGen) and text-to-sound (AudioGen). Use when you need to generate music from text descriptions, create sound effects, or perform melody-conditioned music generation.