A graphic with a blue background featuring the text 'SECTION EVENT' in bold letters, alongside the Audio Engineering Society logo

Location

University of Toronto - Edward Johnson Building
University of Toronto Edward Johnson Building Room 330, 80 Queens Park, Toronto, ON M5S 2C5, Canada

Location

University of Toronto - Edward Johnson Building
University of Toronto Edward Johnson Building Room 330, 80 Queens Park, Toronto, ON M5S 2C5, Canada

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Date

May 28 2024
Expired!

Time

6:30 pm - 9:30 pm

AES Toronto Section Event – Machine Learning – Automation – Artificial Intelligence

The AES Toronto Section invites you to another great event on May 28 at 6:30 p.m. ET.

University of Toronto, Edward Johnson Building, Room 330

Hosted by: 
Anthony Kuzub, Audio Engineering Society: As of 2020 Anthony has been working with the Canadian Broadcasting Corporation to design systems to best implement Audio Engineering Society standards. Leading projects with engineering Solution for the Media technology and infrastructure services. Anthony’s current portfolios include real time and file transport of production audio for radio, television and digital production. Anthony is actively involved in the technical development of audio and media control standards.
Noah Mintz (Presenter)
Arthur Bastos (Presenter)

In an era where technological advancements are revolutionizing every aspect of our lives, the field of audio engineering stands at the forefront of innovation. The Audio Engineering Society invites you to delve into the fascinating world where machine learning, automation, and artificial intelligence converge to shape the future of sound.

This meeting will be a dynamic exploration of the latest developments in applying machine learning algorithms, automation techniques, and AI models to audio engineering practices. From enhancing audio quality to optimizing production workflows, the potential applications are vast and transformative.

Join leading experts as they showcase cutting-edge research, innovative projects, and real-world applications at the intersection of audio engineering and AI. Discover how machine learning algorithms can analyze, process, and synthesize audio data with unprecedented accuracy and efficiency.

Registration is required.

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