A direction-independent latent code learned by an autoencoder lets a small network predict individualized HRTF magnitudes from anthropometric measurements and allows training on multiple datasets.
A wide dataset of ear shapes and pinna- related transfer functions generated by random ear drawings,
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Head-Related Transfer Function Individualization Using Anthropometric Features and Spatially Independent Latent Representation
A direction-independent latent code learned by an autoencoder lets a small network predict individualized HRTF magnitudes from anthropometric measurements and allows training on multiple datasets.