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Dismiss alert {{ message }} DoMusic / Hybrid-Net Public * Notifications * Fork 12 * Star 283 * Real-time audio source separation, generate lyrics, chords, beat. lamucal.ai 283 stars 12 forks Branches Tags Activity Star Notifications * Code * Issues 0 * Pull requests 0 * Actions * Projects 0 * Security * Insights Additional navigation options * Code * Issues * Pull requests * Actions * Projects * Security * Insights DoMusic/Hybrid-Net This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. master BranchesTags Go to file Code Folders and files Name Name Last commit message Last commit date Latest commit History 8 Commits image image python python README.md README.md View all files Repository files navigation * README Hybrid-Net Real-time audio source separation, generate lyrics, chords, beat. A transformer-based hybrid multimodal model, various transformer models address different problems in the field of music information retrieval, these models generate corresponding information dependencies that mutually influence each other. An AI-powered multimodal project focused on music, generate chords, beats, lyrics, melody, and tabs for any song. The online experience, See the site here [tnn] [model] U-Net network model for audio source separation, Pitch-Net, Beat-Net, Chord-Net and Segment-Net based on the transformer model. Apart from establishing the correlation between the frequency and time, the most important aspect is to establish the mutual influence between different networks. The entire AI-powered process is implemented in aitabs.py, while the various network structure models can be referenced in the models folder. Note: U-Net and Segment-Net use the stft spectrum of audio as input. Beat-Net uses three spectrograms of drums, bass, and other instruments as input,Chord-Net uses one spectrogram of the background music. Features * Chord, music chord detection, including major, minor, 7, maj7, min7, 6, m6, sus2, sus4, 5, and inverted chords. Determining the key of a song. * Beat, music beat, downbeat detection and tempo (BPM) tracking * Pitch, tracking the pitch of the melody in the vocal track. * Music Structure, music segment boundaries and labels, include intro, verse, chorus, bridge and etc. * Lyrics, music lyrics recognition and automatic lyrics to audio alignment, use ASR (whisper) to recognize the lyrics of the vocal track. The alignment of lyrics and audio is achieved through fine-tuning the wav2vec2 pre-training model. Currently, it supports dozens of languages, including English, Spanish, Portuguese, Russian, Japanese, Korean, Arabic, Chinese, and more. * AI Tabs, Generate playable sheet music, including chord charts and six-line staves, using chords, beats, music structure information, lyrics, rhythm, etc. It supports editing functionalities for chords, rhythm, and lyrics. * Other, audio source separation, speed adjustment, pitch shifting, etc. For more AI-powered feature experiences, see the website: Lamucal.ai About Real-time audio source separation, generate lyrics, chords, beat. lamucal.ai Resources Readme Activity Custom properties Stars 283 stars Watchers 1 watching Forks 12 forks Report repository Releases No releases published Packages 0 No packages published Languages * Python 100.0% Footer (c) 2024 GitHub, Inc. Footer navigation * Terms * Privacy * Security * Status * Docs * Contact * Manage cookies * Do not share my personal information You can't perform that action at this time.