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Real-Time Chord and Note Detection System for Music Production
  1. case
  2. Real-Time Chord and Note Detection System for Music Production

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Real-Time Chord and Note Detection System for Music Production

jelvix.com
Media
Entertainment

Business Challenges in Music Analysis Automation

Current manual processes for chord and note extraction in music production are time-consuming and error-prone. The industry lacks efficient tools for real-time audio analysis with high accuracy, compounded by limited availability of tagged training data and strict hardware constraints for processing speed.

About the Client

Leading music production facility specializing in innovative audio technology development

Core Project Goals

  • Develop ML algorithm for real-time chord/note detection with 90%+ accuracy
  • Create scalable solution for diverse audio/video inputs
  • Optimize performance under memory/GPU limitations
  • Establish automated workflow for music composition analysis

System Functionality Requirements

  • Audio/video input processing engine
  • Chord and note detection with time-stamping
  • Synchronization with source media
  • Accuracy evaluation dashboard
  • Data augmentation pipeline for training

Technology Stack Requirements

Python 3.7
TensorFlow 1.14.0
Keras 2.3.0
Librosa 0.7
Harmonic Constant-Q Transform

System Integration Needs

  • Digital Audio Workstations (DAWs)
  • Cloud storage APIs
  • GPU acceleration frameworks

Performance Constraints

  • Processing latency under 500ms
  • 90%+ model accuracy on diverse datasets
  • Memory-efficient operations for constrained environments
  • Data privacy compliance for audio content

Expected Business Transformation

Automated music analysis will reduce manual processing time by 70%, enabling creative teams to focus on high-value composition tasks. The solution will establish new industry standards for real-time music processing while enhancing competitive advantage through proprietary ML technology.

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