Results for “audio-separation”

Remove background noise and isolate vocals or speech from audio files using the ElevenLabs Voice Isolator API.

Detect AI-generated audio, images, video, and text, trace synthesis sources, apply watermarks, verify speaker identity, and analyze media intelligence using the Resemble AI platform.

Generates spectrograms and multi-panel audio feature visualizations (mel, chroma, MFCC) from audio files via a Go CLI.

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

Generate spectrograms and audio feature visualizations (mel, chroma, MFCC, tempogram, etc.) from audio files via CLI. Useful for audio analysis, music production debugging, and visual documentation.

Analyzes sound wave propagation, acoustic impedance, resonators, noise insulation, and musical instrument acoustics, with applications in concert halls, sonar, and noise barriers.

Discovers podcasts via the iTunes Search API, parses RSS feeds, downloads audio, transcribes with OpenAI Whisper, chunks transcripts, and upserts results into a database table.

Expert in spatial audio, procedural sound design, game audio middleware, and app UX sound design. Specializes in HRTF/Ambisonics, Wwise/FMOD integration, UI sound design, and adaptive music systems. Activate on 'spatial audio', 'HRTF', 'binaural', 'Wwise', 'FMOD', 'procedural sound', 'footstep system', 'adaptive music', 'UI sounds', 'notification audio', 'sonic branding'. NOT for music composition/production (use DAW), audio post-production for film (linear media), voice cloning/TTS (use voice-audio-engineer), podcast editing (use standard audio editors), or hardware design.

Remove background noise and isolate vocals from audio files using the inference.sh CLI and ElevenLabs voice isolator.

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".

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

Generate spectrograms and audio feature visualizations (mel, chroma, MFCC, tempogram, etc.) from audio files via CLI. Useful for audio analysis, music production debugging, and visual documentation.

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

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

Generate sound effects from text descriptions using ElevenLabs, with support for looping, duration control, and prompt influence tuning.

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.

Transcribe audio files to text with optional speaker diarization and known-speaker hints using OpenAI models.

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

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.

Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features and classifying samples with machine learning models.

用自然语言描述生成目标音频。把一段场景描述（人声对话、环境声、音效、背景音乐等复合音频）一次性生成成音频。当用户描述一个声音场景、要求生成/合成/制作一段音频或声音、给出形如"角色：台词"的对话脚本要转成音频、或要按参考音频的音色说话时使用。支持两种模式：纯文本描述生成（T2A）和带参考音频生成（A2A，在描述中引用参考音频指定角色音色）

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

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

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.

Transcribe and translate speech across 99 languages using OpenAI's Whisper model, with support for multiple model sizes, batch processing, and subtitle generation.

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

Create and modify SoundCue assets — add/connect nodes (mixer, random, delay, attenuation, modulator, etc.) and set audio properties (SoundCueService). Use when the user asks to create a Sound Cue, build a SoundCue node graph, or wire audio playback logic.

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

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

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

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.

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

Multi-project signal isolation with cascading recipe resolution

Batch Signal Isolation with Recipe-Driven Processing

Evaluates speaker verification models by computing true positive rate at fixed false positive rate thresholds, probing embedding space separation of same-speaker versus different-speaker pairs.