Many singers and musicians struggle to translate their vocal melodies into structured chord progressions. While tools exist for analyzing instrumental music, vocal input poses unique challenges due to variations in pitch, vibrato, and phrasing. This gap makes it difficult for vocalists to efficiently develop their musical ideas or collaborate with others.

A Tool for Vocalists to Discover Chords

One approach could be creating an app that analyzes sung or hummed melodies and suggests matching chords. Starting with monophonic (single-note) input, the app could:

• Provide real-time chord identification as the user sings
• Suggest alternative chords that might fit the melody
• Allow exporting chord progressions to standard music formats
• Include explanations of why certain chords work with the melody

The tool could be particularly valuable for songwriters who understand music intuitively but lack formal theory training, as well as educators demonstrating chord-melody relationships.

How It Might Work

An initial version might focus on basic chord detection using existing pitch-tracking technology, then gradually add features:

1. A simple interface recording voice input and identifying basic major/minor chords
2. More sophisticated analysis of sustained notes with adjustable sensitivity for pitch variations
3. Eventual machine learning improvements for handling harmonies and vocal artifacts

Unlike instrument-focused chord detectors, this would specifically address the needs of vocalists, potentially integrating with music production software.

Potential Benefits and Applications

Such a tool could help:

• Rapidly prototype song ideas without needing instruments
• Learn music theory concepts through practical application
• Facilitate collaboration by quickly sharing chord progressions

While similar tools exist for instruments, focusing specifically on vocal input could fill an important gap for many musicians and creators.