Chord ai vs Omnizart

Chord ai is a mobile app that recognizes chords and beats in songs, helping listeners follow music or learn to play it. Songs can be loaded from YouTube, SoundCloud, audio files, or a device microphone. The app detects chords, tracks beats and downbeats, displays tempo and song structure, and infers a song's key; it also shows guitar, piano, and ukulele chord diagrams. Microphone input can identify chords in real time. The maker describes on-device deep learning, with audio files and microphone input analyzed on the phone. The free plan provides basic features with unlimited free use. Chord ai Pro adds recognition of more than 700 chords, voicing and position suggestions, unlimited saved songs, PDF transcription export, score editing, and WAV export of bass, drums, vocals, and other stems. Other Pro tools include pitch shifting, alternate tunings, smart capo suggestions, and processing audio or video up to one hour at once. Pro costs $9 a month or $69 a year, with prices depending on App Store country. The app is available on Android and iOS, and the maker does not provide API access to its technology.

Omnizart is a free Python library for transcribing polyphonic music into pitched instruments, vocal melody, chords, drum events, and beats. Pre-trained checkpoints allow transcription without first training a model. The project also documents dataset downloads, feature preprocessing, model training, transcription, and sonification, with MIDI, CSV, and text output formats. It lists separate applications for music, drums, vocals, vocal contours, chords, and beats, along with chord detection, MIDI export, and stem separation. Installation options include pip, Docker, and Conda, and a command-line interface is provided. Documentation links to a Colab notebook and a Replicate web demo. Omnizart supports Linux, Windows, macOS, and self-hosted setups, but is incompatible with ARM-based macOS because of underlying dependencies. The package requires Python 3.8 or later and below 3.15. Drum checkpoints can be used for transcription, though the drum model has an unresolved issue that prevents loss convergence when training from scratch. It is MIT-licensed and offers GitHub Issues for installation, compatibility, and usage problems.