ApollodB: Emotion‑aware mastering with state‑of‑the‑art deep learning

Powered by models trained on the DEAM dataset, ApollodB maps your track’s emotion in the Valence–Arousal space and exports studio‑grade EQ curves and high‑fidelity EQed audio. No data is stored or used for model training.

          Emotion Intelligence
          Valence–Arousal mapping with confidence
        

          Studio-Grade EQ
          Wavelet/Parametric/Graphic presets
        

          Batch Workflow
          Aggregate analysis & per-track exports
        

Single File

Drag and drop a file here or click to browse

EQ Aggression: 0.5 EQ Style: HQ linear-phase

Warmth: 0.0 Presence: 0.0 Air: 0.0

Curated IEM Database

Explore in-ear monitors (IEMs) aligned with emotion signatures and EQ targets. This section provides a curated list and guidance for pairing EQ with IEM character.

Price

Name	Signature	Valence Match	Price

Note: This is informational and does not alter the model’s behavior.

ApollodB

AI-Powered Music Emotion Analysis & EQ Optimization

By Parikshit Kumar · California · v1.0.0

ApollodB maps audio to the valence–arousal space and derives emotion-aligned EQ curves. The frontend replicates the original Streamlit experience with a modern UI while preserving backend logic.

How it works

Extracts audio features via librosa
Predicts emotions using a TF model with neutral bias handling
Generates EQ targets (Wavelet/Parametric/Graphic)
Applies EQ and exports audio

What’s included

Single & batch analysis
Interactive VA plots & distributions
EQ curves visualization and text export
Per-track EQed audio and spectrograms

ApollodB: Emotion‑aware mastering with state‑of‑the‑art deep learning

Analysis Mode

IEM Database

Curated IEM Database

References

ApollodB

How it works

What’s included

FAQs

EQ Curve

Actions

Aggregate EQ

Individual Downloads