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pop2piano

sweetcocoa

Pop2Piano was proposed in the paper Pop2Piano : Pop Audio-based Piano Cover Generation by Jongho Choi and Kyogu Lee. Piano covers of pop music are widely enjoyed, but generating them from music is not a trivial task. It requires great expertise with playing piano as well as knowing different characteristics and melodies of a song. With Pop2Piano you can directly generate a cover from a song's audio waveform. It is the first model to directly generate a piano cover from pop audio without melody and chord extraction modules. Pop2Piano is an encoder-decoder Transformer model based on T5. The input audio is transformed to its waveform and passed to the encoder, which transforms it to a latent representation. The decoder uses these latent representations to generate token ids in an autoregressive way. Each token id corresponds to one of four different token types: time, velocity, note and 'special'. The token ids are then decoded to their equivalent MIDI file.

Speech recognition

Input Audio→ Output Text

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