Remove BERT Remove Data Scarcity Remove Neural Network
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What AI Music Generators Can Do (And How They Do It)

AssemblyAI

Data scarcity: Paired natural anguage descriptions of music and corresponding music recordings are extremely scarce, in contrast to the abundance of image/descriptions pairs available online, e.g. in online art galleries or social media.  This also makes the evaluation step harder and highly subjective.

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Achieving accurate image segmentation with limited data: strategies and techniques

deepsense.ai

This support set is presented to the neural network, and the expectation is for the network to correctly classify unseen examples of the newly introduced concept. For instance, the analogy of the masked token prediction task used to train BERT is known as masked image modeling in computer vision. Source: [link].

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Achieving accurate image segmentation with limited data: strategies and techniques

deepsense.ai

This support set is presented to the neural network, and the expectation is for the network to correctly classify unseen examples of the newly introduced concept. For instance, the analogy of the masked token prediction task used to train BERT is known as masked image modeling in computer vision. Source: [link].

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AI for Music Generation (Overview)

Viso.ai

Symbolic Music Understanding ( MusicBERT ): MusicBERT is based on the BERT (Bidirectional Encoder Representations from Transformers) NLP model. It addresses issues in traditional end-to-end models, like data scarcity and lack of melody control, by separating lyric-to-template and template-to-melody processes.