Phase 4: Audio & Music Generation · 45 min · Python · pydub · librosa

Audio Post-Processing & Mastering

Normalization, mixing, mastering — making generated audio production-ready is an engineering discipline, not an afterthought.

Real-world application: Audio post-processing (normalization, mixing, mastering, format conversion) demonstrates you understand the full audio delivery pipeline, not just generation.

What you will learn

Implement audio normalization: loudness standarding (LUFS), peak normalization
Mix multiple audio tracks: balancing dialogue, music, SFX levels
Apply mastering: EQ, compression, stereo widening for final polish
Handle format conversion and delivery: WAV master, MP3/Opus for streaming

Objective

Generate listening samples and evaluate them for structure, fidelity, editability, and intended use. In the paired studio lab, build a post-processing pipeline that takes a generated audio track and applies: (1) loudness normalization to -14 LUFS (streaming standard), (2) EQ adjustment, (3) compression, (4) format conversion to MP3 and Opus. Measure loudness before and after processing.

The Problem

A team generates audio for a product video: background music from Stable Audio, narration from ElevenLabs TTS, and SFX from Stable Audio Open. They merge them all at their default volumes. The result is unlistenable:

The music is too loud — it drowns out the narration
The SFX peaks clip — causing distortion
The overall loudness is inconsistent — quiet in some parts, loud in others
The final MP3 sounds different on different devices

They need audio post-processing: normalization, mixing, and mastering to make the audio production-ready.

What you'll build
Implement audio normalization (LUFS and peak), mix multiple audio tracks (dialogue, music, SFX) with proper level balancing, apply mastering (EQ, compression), and handle format conversion for delivery.

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Key terms in this lesson

Streaming