music transcription

**Music transcription** uses **AI to convert audio recordings into sheet music or MIDI** — automatically detecting notes, rhythms, chords, and instruments from audio, enabling musicians to learn songs, create arrangements, and analyze music without manual transcription. **What Is Music Transcription?** - **Definition**: AI conversion of audio to musical notation. - **Input**: Audio recordings (MP3, WAV). - **Output**: Sheet music, MIDI files, chord charts, tabs. - **Goal**: Accurate note-by-note representation of music. **Transcription Tasks** **Melody Transcription**: Extract main tune, single-note line. **Polyphonic Transcription**: Multiple simultaneous notes (piano, guitar). **Chord Recognition**: Identify chord progressions. **Drum Transcription**: Detect drum hits, patterns. **Multi-Instrument**: Separate and transcribe each instrument. **AI Techniques** **Pitch Detection**: Identify fundamental frequencies, overtones. **Onset Detection**: Find note start times. **Source Separation**: Isolate instruments before transcription. **Deep Learning**: CNNs on spectrograms, RNNs for temporal patterns. **Music Language Models**: Transformers for musical context. **Challenges**: Polyphonic music (multiple notes), overlapping instruments, audio quality, expressive timing, ornaments. **Applications**: Learning songs, creating sheet music, music analysis, copyright detection, music education. **Tools**: AnthemScore, ScoreCloud, Melodyne, Transcribe!, MuseScore, Sonic Visualiser.