Generative model blends query input with latent states for structured improvisation.
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5 results for “improvisation”
problem Generating structured music from latent states of a neural network.
method Used a Variational Autoencoder (VAE) trained on a specific style corpus, and controlled blending with a noisy channel.
result Generated music with longer-term structure that blends query input with network style.
Piano Geniecs.LG
We present Piano Genie, an intelligent controller which allows non-musicians to improvise on the piano. With Piano Genie, a user performs on a simple interface with eight buttons, and their performance is decoded into the space of plausible piano music in real time. To learn a suitable mapping procedure for this proble…
Proposes SPCA to incorporate structural constraints in model identification.
problem Model identification with partial structural knowledge.
method Structural Principal Component Analysis (SPCA) that leverages structural information.
result Demonstrates improved model estimates using synthetic and industrial data.
Deep Autotuner corrects singing pitch using neural networks.
problem Automatic pitch correction for singing performances.
method Neural network model trained on spectrograms of singing and accompaniment.
result Neural network predicts continuous pitch shifts, allowing for improvisation and harmonization.
Automated EEG analysis gauges mental workload in task evaluation.
problem Evaluating mental workload in user tasks, especially complex ones.
method Experimental setup, EEG data analysis, feature extraction, machine learning.
result Machine learning outperforms traditional methods in mental workload estimation.