, this model’s overall structure is based on other models, which combine MuLan + AudioLM and MuLan + w2b-Bert + Soundstream.is a text-music joint embedding model with contrastive training and 44M music audio-text description pair from YouTube;w2v-BERT
is a Bidirectional Encoder Representation from Transformers, a deep learning tool originally for speech, this time used for audio;Google combined all of this to generate music from text. Here’s how the researchers explain MusicLM:‘a calming violin melody backed by a distorted guitar riff ‘. MusicLM casts the process of conditional music generation as a hierarchical sequence-to-sequence modeling task, and it generates music at 24 kHz that remains consistent over several minutes. Our experiments show that MusicLM outperforms previous systems both in audio quality and adherence to the text description.
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