audio-voice-recovery

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---
name: audio-voice-recovery
description: Audio forensics and voice recovery guidelines for CSI-level audio analysis. This skill should be used when recovering voice from low-quality or low-volume audio, enhancing degraded recordings, performing forensic audio analysis, or transcribing difficult audio. Triggers on tasks involving audio enhancement, noise reduction, voice isolation, forensic authentication, or audio transcription.
---

# Forensic Audio Research Audio Voice Recovery Best Practices

Comprehensive audio forensics and voice recovery guide providing CSI-level capabilities for recovering voice from low-quality, low-volume, or damaged audio recordings. Contains 45 rules across 8 categories, prioritized by impact to guide audio enhancement, forensic analysis, and transcription workflows.

## When to Apply

Reference these guidelines when:
- Recovering voice from noisy or low-quality recordings
- Enhancing audio for transcription or legal evidence
- Performing forensic audio authentication
- Analyzing recordings for tampering or splices
- Building automated audio processing pipelines
- Transcribing difficult or degraded speech

## Rule Categories by Priority

| Priority | Category | Impact | Prefix | Rules |
|----------|----------|--------|--------|-------|
| 1 | Signal Preservation & Analysis | CRITICAL | `signal-` | 5 |
| 2 | Noise Profiling & Estimation | CRITICAL | `noise-` | 5 |
| 3 | Spectral Processing | HIGH | `spectral-` | 6 |
| 4 | Voice Isolation & Enhancement | HIGH | `voice-` | 7 |
| 5 | Temporal Processing | MEDIUM-HIGH | `temporal-` | 5 |
| 6 | Transcription & Recognition | MEDIUM | `transcribe-` | 5 |
| 7 | Forensic Authentication | MEDIUM | `forensic-` | 5 |
| 8 | Tool Integration & Automation | LOW-MEDIUM | `tool-` | 7 |

## Quick Reference

### 1. Signal Preservation & Analysis (CRITICAL)

- [`signal-preserve-original`](references/signal-preserve-original.md) - Never modify original recording
- [`signal-lossless-format`](references/signal-lossless-format.md) - Use lossless formats for processing
- [`signal-sample-rate`](references/signal-sample-rate.md) - Preserve native sample rate
- [`signal-bit-depth`](references/signal-bit-depth.md) - Use maximum bit depth for processing
- [`signal-analyze-first`](references/signal-analyze-first.md) - Analyze before processing

### 2. Noise Profiling & Estimation (CRITICAL)

- [`noise-profile-silence`](references/noise-profile-silence.md) - Extract noise profile from silent segments
- [`noise-identify-type`](references/noise-identify-type.md) - Identify noise type before reduction
- [`noise-adaptive-estimation`](references/noise-adaptive-estimation.md) - Use adaptive estimation for non-stationary noise
- [`noise-snr-assessment`](references/noise-snr-assessment.md) - Measure SNR before and after
- [`noise-avoid-overprocessing`](references/noise-avoid-overprocessing.md) - Avoid over-processing and musical artifacts

### 3. Spectral Processing (HIGH)

- [`spectral-subtraction`](references/spectral-subtraction.md) - Apply spectral subtraction for stationary noise
- [`spectral-wiener-filter`](references/spectral-wiener-filter.md) - Use Wiener filter for optimal noise estimation
- [`spectral-notch-filter`](references/spectral-notch-filter.md) - Apply notch filters for tonal interference
- [`spectral-band-limiting`](references/spectral-band-limiting.md) - Apply frequency band limiting for speech
- [`spectral-equalization`](references/spectral-equalization.md) - Use forensic equalization to restore intelligibility
- [`spectral-declip`](references/spectral-declip.md) - Repair clipped audio before other processing

### 4. Voice Isolation & Enhancement (HIGH)

- [`voice-rnnoise`](references/voice-rnnoise.md) - Use RNNoise for real-time ML denoising
- [`voice-dialogue-isolate`](references/voice-dialogue-isolate.md) - Use source separation for complex backgrounds
- [`voice-formant-preserve`](references/voice-formant-preserve.md) - Preserve formants during pitch manipulation