Timezone: »
Audio scene understanding, parsing sound into a hierarchy of meaningful parts, is an open problem in representation learning. Sound is a particularly challenging domain due to its high dimensionality, sequential dependencies and hierarchical structure. Differentiable Digital Signal Processing (DDSP) greatly simplifies the forward problem of generating audio by introducing differentiable synthesizer and effects modules that combine strong signal priors with end-to-end learning. Here, we focus on the inverse problem, inferring synthesis parameters to approximate an audio scene. We demonstrate that DDSP modules can enable a new approach to self-supervision, generating synthetic audio with differentiable synthesizers and training feature extractor networks to infer the synthesis parameters. By building a hierarchy from sinusoidal to harmonic representations, we show that it possible to use such an inverse modeling approach to disentangle pitch from timbre, an important task in audio scene understanding.
Link to the video: https://slideslive.com/38930745/selfsupervised-pitch-detection-by-inverse-audio-synthesis
Author Information
Jesse Engel (Google Brain)
More from the Same Authors
-
2022 Poster: General-purpose, long-context autoregressive modeling with Perceiver AR »
Curtis Hawthorne · Drew Jaegle · Cătălina Cangea · Sebastian Borgeaud · Charlie Nash · Mateusz Malinowski · Sander Dieleman · Oriol Vinyals · Matthew Botvinick · Ian Simon · Hannah Sheahan · Neil Zeghidour · Jean-Baptiste Alayrac · Joao Carreira · Jesse Engel -
2022 Spotlight: General-purpose, long-context autoregressive modeling with Perceiver AR »
Curtis Hawthorne · Drew Jaegle · Cătălina Cangea · Sebastian Borgeaud · Charlie Nash · Mateusz Malinowski · Sander Dieleman · Oriol Vinyals · Matthew Botvinick · Ian Simon · Hannah Sheahan · Neil Zeghidour · Jean-Baptiste Alayrac · Joao Carreira · Jesse Engel -
2020 Poster: Encoding Musical Style with Transformer Autoencoders »
Kristy Choi · Curtis Hawthorne · Ian Simon · Monica Dinculescu · Jesse Engel -
2019 Poster: Learning to Groove with Inverse Sequence Transformations »
Jon Gillick · Adam Roberts · Jesse Engel · Douglas Eck · David Bamman -
2019 Oral: Learning to Groove with Inverse Sequence Transformations »
Jon Gillick · Adam Roberts · Jesse Engel · Douglas Eck · David Bamman -
2018 Poster: A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music »
Adam Roberts · Jesse Engel · Colin Raffel · Curtis Hawthorne · Douglas Eck -
2018 Oral: A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music »
Adam Roberts · Jesse Engel · Colin Raffel · Curtis Hawthorne · Douglas Eck -
2017 Poster: Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders »
Cinjon Resnick · Adam Roberts · Jesse Engel · Douglas Eck · Sander Dieleman · Karen Simonyan · Mohammad Norouzi -
2017 Talk: Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders »
Cinjon Resnick · Adam Roberts · Jesse Engel · Douglas Eck · Sander Dieleman · Karen Simonyan · Mohammad Norouzi