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Developing Creativity with AI & DL for Sound & Audio, with Valerio Velardo, E28

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Manage episode 298713890 series 2624979
Content provided by Alexandra Petrus. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Alexandra Petrus or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
  • 2:10 - Using AI to augment and reshape creativity in a modern world. Psychological creativity and story creativity - can an AI model help AI music artists, today, get off their creative blocks?
  • 12:15 - Attempt to define ‘good’ music, using a cognitive music literature background.
  • 17:00 - Are we better or worse off, for AI in audio/music? Is it sustainable for the effort input and cost, impact and efficiency output?
  • 22:35 - ‘Deep Nostalgia” from myheritage initiative, and GPT-J - looking for strengths in the two approaches.
  • 29:25 - The Sound of AI community - a HuggingFace version for audio?
  • 31:15 - Train a DL - CNN sound classifier built with Pytorch and torchaudio on the Urban Sound 8k dataset.
  • 35:00 - Is deep learning a dead end for artificial intelligence?
  • 38:05 - Could someone that is a pure tech profile ever be in such an intersection in sync with the artistic world? Is it a pre-req to be domain savvy to build AI audio solutions?
  • 42:10 - Helping music tech companies with a focus on audio (voice, speech, sound), the experience so far.
  • 49:45 - Hard problems to solve when dealing with AI audio - Top three.
  • 56:50 - First piece of music composed by a machine.

References:

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33 episoade

Artwork
iconDistribuie
 
Manage episode 298713890 series 2624979
Content provided by Alexandra Petrus. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Alexandra Petrus or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
  • 2:10 - Using AI to augment and reshape creativity in a modern world. Psychological creativity and story creativity - can an AI model help AI music artists, today, get off their creative blocks?
  • 12:15 - Attempt to define ‘good’ music, using a cognitive music literature background.
  • 17:00 - Are we better or worse off, for AI in audio/music? Is it sustainable for the effort input and cost, impact and efficiency output?
  • 22:35 - ‘Deep Nostalgia” from myheritage initiative, and GPT-J - looking for strengths in the two approaches.
  • 29:25 - The Sound of AI community - a HuggingFace version for audio?
  • 31:15 - Train a DL - CNN sound classifier built with Pytorch and torchaudio on the Urban Sound 8k dataset.
  • 35:00 - Is deep learning a dead end for artificial intelligence?
  • 38:05 - Could someone that is a pure tech profile ever be in such an intersection in sync with the artistic world? Is it a pre-req to be domain savvy to build AI audio solutions?
  • 42:10 - Helping music tech companies with a focus on audio (voice, speech, sound), the experience so far.
  • 49:45 - Hard problems to solve when dealing with AI audio - Top three.
  • 56:50 - First piece of music composed by a machine.

References:

  continue reading

33 episoade

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