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HomeLLMsacestep captioner

acestep captioner

by ACE-Step

Open source · 2k downloads · 46 likes

2.1
(46 reviews)AudioAPI & Local
About

The ACE-Step Captioner is an AI model specialized in generating detailed and structured descriptions of musical content. It excels in analyzing styles, instruments, structures, and sound characteristics, delivering greater precision than solutions like Gemini Pro 2.5. With its rich vocabulary and ability to identify over 1,000 instruments and descriptive terms, it produces professional annotations tailored to diverse needs. This model is particularly useful for training music AI systems, creating metadata for audio databases, and music education. Its holistic approach makes it a versatile tool for documenting, analyzing, and categorizing music with remarkable nuance.

Documentation

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:

Arduino
*Task* Describe this audio in detail
<audio>

Output Format

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

Example Output

CSS
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)

CategoryStyles
ElectronicAmbient, Techno, House, Drum & Bass, Synthwave, IDM, Downtempo
RockAlternative, Indie, Post-Rock, Progressive, Psychedelic, Grunge
PopSynth-pop, Electropop, Dream Pop, Art Pop, Indie Pop
ClassicalOrchestral, Chamber, Minimalist, Neo-Classical, Cinematic
WorldLatin, African, Middle Eastern, Asian Traditional, Celtic
JazzFusion, Smooth, Bebop, Modal, Free Jazz
Hip-HopTrap, Boom Bap, Lo-fi, Instrumental, Cloud Rap

Instruments (1000+ Supported)

CategoryExamples
StringsAcoustic Guitar, Electric Guitar, Violin, Cello, Bass, Harp, Mandolin
KeysPiano, Synthesizer, Organ, Rhodes, Wurlitzer, Mellotron
PercussionDrums, Electronic Drums, Congas, Bongos, Timpani, Vibraphone
WindSaxophone, Trumpet, Flute, Clarinet, Oboe, French Horn
ElectronicSynth Bass, Pad, Lead, Arpeggiator, Sampler, 808, 303

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

DimensionDescriptors
TextureWarm, Bright, Dark, Crisp, Muddy, Clean, Distorted, Saturated
SpaceReverberant, Dry, Spacious, Intimate, Cavernous, Tight
DynamicsPunchy, Soft, Aggressive, Gentle, Compressed, Dynamic
CharacterEthereal, Gritty, Smooth, Raw, Polished, Organic, Synthetic

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
Capabilities & Tags
transformerssafetensorsqwen2_5_omnitext-to-audiomusicaudioendpoints_compatible
Links & Resources
Specifications
CategoryAudio
AccessAPI & Local
LicenseOpen Source
PricingOpen Source
Rating
2.1

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