SYNAPSEai1 / SynapseMusicV12-Captioner

Tech Report

ACE-Step Captioner

Description

ACE-Step Captioner is the annotation model used by ACE-Step v1.5 for training data labeling. It is a professional-grade music captioning model that generates detailed, structured descriptions of audio content.

Performance

🏆 Accuracy surpasses Gemini Pro 2.5 in music description tasks

Key Features

• 🎼 Musical Style Analysis - Identifies genres, sub-genres, and stylistic influences
• 🎸 Instrument Recognition - Detects and describes 1000+ instrument types and combinations
• 🎭 Structure & Progression - Analyzes musical arrangement including intro, verse, chorus, bridge, climax, and outro
• 🔊 Timbre Description - Captures tonal qualities, textures, and sonic characteristics
• 📝 Rich Vocabulary - Supports 1000+ descriptive terms for comprehensive music annotation

Usage

The usage is the same as Qwen2.5 Omni-7B .

Prompt Format

Use the following prompt to caption audio:

*Task* Describe this audio in detail
<audio>

Output Format

The model generates natural language descriptions covering multiple aspects of the music.

Example Output

A melancholic indie folk track featuring fingerpicked acoustic guitar 
as the primary instrument. The song opens with a sparse, contemplative 
intro before the vocals enter with a breathy, intimate delivery. 
The arrangement gradually builds through the verse, adding subtle 
string pads and a gentle kick drum. The chorus lifts with layered 
harmonies and a warmer, fuller texture. The bridge introduces a 
key change and emotional climax before returning to the stripped-down 
acoustic arrangement for the outro.

Descriptive Capabilities

Musical Styles (Examples)

Instruments (1000+ Supported)

Structure Analysis

• Intro / Outro - Opening and closing sections
• Verse / Pre-Chorus / Chorus - Main song structure
• Bridge / Break - Transitional sections
• Build-up / Drop / Climax - Dynamic progression
• Interlude / Solo - Instrumental passages

Timbre Descriptions

Use Cases

• Music AI Training - Generate high-quality captions for music generation models
• Music Information Retrieval - Create searchable metadata for audio databases
• Content Moderation - Analyze and categorize music content
• Music Education - Provide detailed analysis for learning purposes
• Audio Production - Document and describe sound design elements