6/16/2023 0 Comments Transformer en pdf en wordAnd, we employ it to learn to compose expressive Pop piano music That the resulting model can be viewed as a learner over dynamic directed Neighboring tokens, greatly reducing the length of the token sequences. With an expansion-compression trick, weĬonvert a piece of music to a sequence of compound words by grouping New Transformer decoder architecture that uses different feed-forward heads to The type of the tokens, such as note types and metric types. Present a conceptually different approach that explicitly takes into account In the same way as modeling words in natural languages. May possess different properties, existing models usually treat them equally, Separate tokens to indicate the note's pitch, duration, velocity (dynamics),Īnd placement (onset time) along the time grid. For example, to describe a musical note, one needs Tasks, one has to represent a piece of music by a sequence of tokens drawn fromĪ finite set of pre-defined vocabulary. Authors: Wen-Yi Hsiao, Jen-Yu Liu, Yin-Cheng Yeh, Yi-Hsuan Yang Download PDF Abstract: To apply neural sequence models such as the Transformers to music generation
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