Tag: AI

Responsible AI for Offline Plugins – Tamper-Resistant Neural Audio Watermarking – Kanru Hua – ADC 2024

https://audio.dev/ -- @audiodevcon​
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Responsible AI for Offline Plugins - Tamper-Resistant Neural Audio Watermarking - Kanru Hua - ADC 2024
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In the era of rapid generative AI advancements, how do audio plugin developers harness the power of deep learning, while safeguarding against misuses and ensuring regulatory compliance? Existing audio watermarking algorithms are designed to run on the cloud, and when deployed offline, are trivial to bypass when faced against experienced hackers. In this talk, I introduce an innovative algorithm developed for Vocoflex, our AI powered voice transformation plugin. Instead of first generating the voice and then adding the watermark in a post-processing step, our approach involves an end-to-end trained neural network that generates voices with inaudible watermarks already embedded. Furthermore, the neural network resists tampering by 'self-destructing' to contaminate outputs upon malicious perturbation of the network weights. We will share our methodology and provide guidelines for designing similar, but not identical watermarking schemes that tightly couple program logic with watermarks, resilient to both audio manipulations and reverse engineering attempts.
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Slides: https://data.audio.dev/talks/2024/responsible-ai-for-offline-plugins/slides.pdf
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Kanru Hua

In short and above everything else, I make vocal synthesizers! I am so into making the best sounding vocal synthesizer that it took me 13 years to self-teach all the maths and engineering and coding. I now run Tokyo-based audio software manufacturer Dreamtonics.
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ADC is an annual event celebrating all audio development technologies, from music applications and game audio to audio processing and embedded systems. ADC’s mission is to help attendees acquire and develop new audio development skills, and build a network that will support their audio developer career.
Annual ADC Conference - https://audio.dev/
https://www.linkedin.com/company/audiodevcon

https://facebook.com/audiodevcon
https://instagram.com/audiodevcon
https://www.reddit.com/r/audiodevcon/
https://mastodon.social/@audiodevcon
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Streamed & Edited by Digital Medium Ltd: https://online.digital-medium.co.uk
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Organized and produced by JUCE: https://juce.com/
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Special thanks to the ADC24 Team:

Sophie Carus
Derek Heimlich
Andrew Kirk
Bobby Lombardi
Tom Poole
Ralph Richbourg
Jim Roper
Jonathan Roper
Prashant Mishra

#ai #plugins #plugin #adc #audiodev #dsp #audio #conferenceaudio #audioprocessing #audioproduction #audioprogramming #soundtech #audiotech #audiotechnology

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Roland’s Holistic Approach to AI for Music Creation – Paul McCabe, Ichiro Yazawa & Kazuyoshi Sasamori – ADC 2024

https://audio.dev/ -- @audiodevcon​
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Roland’s Holistic Approach to AI for Music Creation - Paul McCabe, Ichiro Yazawa & Kazuyoshi Sasamori - ADC 2024
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This presentation introduces Roland's approach to AI for music creation and will include a technical demonstration of a new AI-powered application. Roland will also overview its holistic strategy for AI which considers R&D, policy, and governance mechanisms. As a general-purpose disruptive technology, Artificial Intelligence is in the process of impacting virtually every aspect of life, including creativity. As a leading music technology innovator, Roland is highly optimistic about the potential of AI to enhance and empower human music making but is deeply aware of the need to innovate responsibly.
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Slides: https://data.audio.dev/talks/2024/rolands-holistic-approach-to-ai-for-music-creation/slides.pdf
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Paul McCabe

Paul McCabe is the SVP of Research and Innovation and leader of Roland Future Design Lab, Roland’s horizon-scanning R&D group. In more than 30 years with Roland, Paul has held positions in product management, marketing, and served as the President & CEO of Roland Canada before relocating from Vancouver to Los Angeles with his family in 2017. As the leader of Roland Future Design Lab (RFDL), Paul oversees a growing team of engineers and technologists exploring the frontiers of emerging tech, trends, and shifts in creative culture around the world. Paul is a family man, composer, sound designer, and lover of science fiction and ice hockey.
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Ichiro Yazawa

Ichiro Yazawa has worked in product development for music production and connectivity technology development such as USB, IEEE1394, Ethernet Audio, Bluetooth, Wi-Fi and MIDI 2.0. Through supporting development of Audio, MIDI, the USB layer, and standard drivers for major operating systems, I have had many friends all over the world who are full of irreplaceable ideas and skills.

In recent years, I have been responsible for a wide range of research and development including AI, Web3, IoT, and Cyber Security. I have been meeting friends with more diverse talents and following paths to new possibilities.

Personally, I enjoy listening to ambient music and playing keyboard on weekends.
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Kazuyoshi Sasamori

I studied signal processing, information processing, and computer architecture at university, and have been working as an engineer at Roland for many years since then. I have been involved in the development of pianos, drums, and synthesizers, focusing on hardware design and sound system design. I have also spent time at BOSS team, working on guitar products.
Some of my memorable projects include the speaker system for the V-Piano Grand and the noise reduction for V-Drums. In recent years, I have served as a Product Manager, planning and developing synthesizers such as the JUNO-DS, RD-2000, and FANTOM/FANTOM-0. Following that, I took on the role of technology development in the R&D department, and I am currently leading research and development as an AI Product Manager at the Roland Future Design Lab, with a focus on the utilization and implementation of AI. The future looks incredibly exciting. Personally, I am an avid fan of synthesizers and rhythm machines, and I love being surrounded by a plethora of hardware—sometimes I feel like my body is made of electronic sounds. However, I also appreciate Jazz and Acoustic music. In my free time, I enjoy outdoor activities and spending time with my dog.
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ADC is an annual event celebrating all audio development technologies, from music applications and game audio to audio processing and embedded systems. ADC’s mission is to help attendees acquire and develop new audio development skills, and build a network that will support their audio developer career.
Annual ADC Conference - https://audio.dev/
https://www.linkedin.com/company/audiodevcon

https://facebook.com/audiodevcon
https://instagram.com/audiodevcon
https://www.reddit.com/r/audiodevcon/
https://mastodon.social/@audiodevcon
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Streamed & Edited by Digital Medium Ltd: https://online.digital-medium.co.uk
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Organized and produced by JUCE: https://juce.com/
---

Special thanks to the ADC24 Team:

Sophie Carus
Derek Heimlich
Andrew Kirk
Bobby Lombardi
Tom Poole
Ralph Richbourg
Jim Roper
Jonathan Roper
Prashant Mishra

#roland #ai #adc #audiodev #audio #conferenceaudio #audioprocessing #audioproduction #audioprogramming #music #musictech #soundtech #audiotech #audiotechnology

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Teaching Audio Developers How to Build AI-Enhanced Audio Plugins – Matthew Yee-King – ADCx Gather 2024

https://audio.dev/ -- @audiodevcon​
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Teaching Audio Developers How to Build AI-Enhanced Audio Plugins - Matthew Yee-King - ADC 2024
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In this talk I will reflect on my experience as an educator, developer and musician working with AI and music technology. I have used many technologies, from Java applets to SuperCollider, Web Audio API and onto C++ and JUCE. I will then describe an educationally focused workflow for the development of AI-enhanced audio plugins that I am currently using for teaching and research/ development work. The workflow utilises C++, JUCE, CMake, PyTorch and RTNeural and has been designed to support educators, students and developers who wish to learn about the integration of AI and machine learning technology into real-time audio applications. I will also present various example plugins I have built using the workflow: a MIDI improviser, a neural network synthesizer controller and neural effects unit.
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Matthew Yee-King

Matthew Yee-King is a professor in the Department of Computing at Goldsmiths, University of London, and served as a visiting professor at the Politecnico di Milano in 2024. He is the programme director for the UoL Worldwide Computer Science Programme, launched in 2019 as the first undergraduate programme on the Coursera platform, which has since attracted nearly 10,000 students from 125 countries. His research focuses on education technology, particularly AI-enhanced systems, and the application of AI to digital signal processing and music performance. In 2024, his book "Build AI-enhanced Audio Plugins with C++" was published by Routledge. Additionally, Matthew is an accomplished musician who has performed, recorded, and collaborated with internationally renowned jazz and electronic musicians such as Aphex Twin, Tom Skinner (Smile band), Matthew Herbert, and Squarepusher.
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ADC is an annual event celebrating all audio development technologies, from music applications and game audio to audio processing and embedded systems. ADC’s mission is to help attendees acquire and develop new audio development skills, and build a network that will support their audio developer career.
Annual ADC Conference - https://audio.dev/
https://www.linkedin.com/company/audiodevcon
https://twitter.com/audiodevcon
https://facebook.com/audiodevcon
https://instagram.com/audiodevcon
https://www.reddit.com/r/audiodevcon/
https://mastodon.social/@audiodevcon
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Streamed & Edited by Digital Medium Ltd: https://online.digital-medium.co.uk
---

Organized and produced by JUCE: https://juce.com/
---

Special thanks to the ADCxGather Team:

Sophie Carus
Derek Heimlich
Andrew Kirk
Bobby Lombardi
Tom Poole
Ralph Richbourg
Jim Roper
Jonathan Roper
Prashant Mishra

#ai #audioplugins #adc #audiodev #dsp #audio #conferenceaudio #audioprocessing #audioproduction #audioprogramming #musictech #soundtech #audiotech #audiotechnology

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Interfaces are King! – A Practical Look at AI Audio Tools and What Audio Professionals Actually Need – Andrew Scheps

https://audio.dev/ -- @audiodevcon​
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Keynote: Interfaces are King! - A Practical Look at AI Audio Tools and What Audio Professionals Actually Need - Andrew Scheps - ADC 2024
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Technology in audio software has progressed immensely in the last few years, especially in the use of LLM AI in audio processing and stem separation. This talk will focus on the current uses of AI in audio tools; a practical look at what professionals actually need; and, possibly most importantly, how the technology should be presented to non-technical users in the industry. There will also be discussion of the necessity for quality data sets as well as some of the legal ramifications of using them.
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Andrew Scheps

Andrew Scheps has engineered and mixed some of the biggest bands in the world: Green Day, Red Hot Chili Peppers, Weezer, Audioslave, Black Sabbath, Metallica, Linkin Park, Hozier, Kaleo and U2. He’s worked with legends such as Johnny Cash, Neil Diamond and Iggy Pop, as well as indie artists such as Low Roar, My Brightest Diamond, Motorpsycho, Rancid, Manu Chao, Tinariwen, Farao, CRX, Cass McCombs and Blood Red Shoes.

Andrew has been awarded Grammys for his work with Adele, Red Hot Chili Peppers and Ziggy Marley, nominated for Best Engineered Album, Classical for his work on The Blue Hour as well as garnering over 20 nominations in categories such as Best Rock Song, Best Rock Album and Best Hard Rock Performance. In addition, Andrew was named International Engineer of the Year Award by the UK’s Music Producers Guild.

In 2011 Andrew started Tonequake Records, a boutique indie label with acts including Low Roar, Favez, Fellow Robot, Act Rights, and Jeff Babko.

After 25 years in Los Angeles, Andrew relocated to the UK in July 2015 where he set up his own mix room which is now equipped for Dolby Atmos Music. He has collaborated on several plugins with Waves and develops custom software for controlling Pro Tools to make his life easier.
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ADC is an annual event celebrating all audio development technologies, from music applications and game audio to audio processing and embedded systems. ADC’s mission is to help attendees acquire and develop new audio development skills, and build a network that will support their audio developer career.
Annual ADC Conference - https://audio.dev/
https://www.linkedin.com/company/audiodevcon

https://facebook.com/audiodevcon
https://instagram.com/audiodevcon
https://www.reddit.com/r/audiodevcon/
https://mastodon.social/@audiodevcon
---

Streamed & Edited by Digital Medium Ltd: https://online.digital-medium.co.uk
---

Organized and produced by JUCE: https://juce.com/
---

Special thanks to the ADCxGather Team:

Sophie Carus
Derek Heimlich
Andrew Kirk
Bobby Lombardi
Tom Poole
Ralph Richbourg
Jim Roper
Jonathan Roper
Prashant Mishra

#adc #ai #aiaudio #audiodev #dsp #audio #audioprocessing #audioproduction #audioprogramming #music #musictech #soundtech #audiotech #audiotechnology

Filed under: UncategorizedTagged with: , , ,

Workshop: Practical Machine Learning – Embed a Generative AI Model in Your App – by @dynamic_cast – ADC 2024

https://audio.dev/ -- @audiodevcon​
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Workshop: Practical Machine Learning - Embed a generative AI model in your app and train your own interactions with it - Anna Wszeborowska, Harriet Drury, Sohyun Im, Julia Läger & Pauline Nemchak - ADC 2024
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In this workshop we’ll explore the fundamentals of Machine Learning. We will run through an easy to follow machine learning model that will:

Be easy for beginners
Run on the CPU
Be real time

This will cover an intro to Machine Learning, small vs large models and an introduction to a training environment in python. We aim to make this workshop as interactive as possible, with the idea of having a trained model in session for everyone to use/play with.

This will be a self-contained workshop aiming to be accessible to all levels of learning - all elements used in the practical part of the workshop will be thoroughly explained in the introduction.
Dynamic Cast - Who Are We?
Dynamic Cast is a peer-to-peer C++ study group, a safe space for underrepresented groups (women, LGBTQIA+, minority ethnic). The Dynamic Cast workshop at ADC is designed to create an entry point to the industry for newcomers, everyone is welcome.
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Slides: https://data.audio.dev/talks/2024/practical-machine-learning/slides.pdf
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Anna Wszeborowska

Anna is an independent software developer and consultant working on interactive real-time systems for music and audio. She is also an academic researcher focusing on exploring strategies for aiding musical self-expression with machine learning. During her time at Ableton she held the role of Technical Principal for Max for Live, worked on the hardware instrument Push and contributed to some of the flagship instruments available in the DAW Live and iOS app Note. Anna has founded programming initiatives helping people underrepresented in tech advance in the field. Currently co-organises a peer-to-peer C++ study group called Dynamic Cast.
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Harriet Drury

Harriet is a Software Engineer at Native Instruments, working on iZotope branded products. She has a keen interest in DSP and ML, having written a proof of concept inference engine in Cmajor. Most recent work in ML has been on real time applications of large libraries.

Plays guitar (occasionally), can hit drums sometimes on time. Harriet co-organises Dynamic Cast, a C++ learning group for underrepresented groups. There are chapters in Berlin and London, with the option to join online, too.
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Sohyun Im

Sohyun Im graduated with a Bachelor's degree in Sound Engineering from the University of West London and is currently pursuing her Master's in Sound and Music Computing at Queen Mary University of London.

She has a keen interest in audio programming and DSP, having conducted research on Virtual Analog Modelling, which bridges the analog and digital realms, during her undergraduate studies. Additionally, she is deeply interested in the emerging field of generative music AI and is dedicated to advancing her knowledge in this area.

Sohyun is also a lifelong pianist. Regardless of the genre, feel free to invite her whenever you need a pianist.
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Julia Läger

Julia is a Software Developer with 7+ years experience writing C++ production code, working previously in automotive and now in music tech at Focusrite. But she also really likes Python. She's currently working on internal tooling, which involves a potpourri of domains and technologies, going from high-level desktop applications down to embedded libraries. She's passionate about music and science, and actually has a background in experimental nano physics.
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Pauline Nemchak

A front-end engineer, music and audio industries enthusiast and linguaphile (aren't we all).
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ADC is an annual event celebrating all audio development technologies, from music applications and game audio to audio processing and embedded systems. ADC’s mission is to help attendees acquire and develop new audio development skills, and build a network that will support their audio developer career.
Annual ADC Conference - https://audio.dev/
https://www.linkedin.com/company/audiodevcon

https://facebook.com/audiodevcon
https://instagram.com/audiodevcon
https://www.reddit.com/r/audiodevcon/
https://mastodon.social/@audiodevcon
---

Streamed & Edited by Digital Medium Ltd: https://online.digital-medium.co.uk
---

Organized and produced by JUCE: https://juce.com/
---

Special thanks to the ADC24 Team:

Sophie Carus
Derek Heimlich
Andrew Kirk
Bobby Lombardi
Tom Poole
Ralph Richbourg
Jim Roper
Jonathan Roper
Prashant Mishra

#machinelearning #machinelearningapplications #ai #adc #audiodev #audio #machinelearningwithpython #audioprocessing #audioproduction #audioprogramming #musictech #soundtech #audiotech #audiotechnology

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GPU Based Audio Processing Platform with AI Audio Effects – Simon Schneider – ADCxGather 2024

https://audio.dev/ -- @audiodevcon​
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GPU Based Audio Processing Platform with AI Audio Effects - Are GPUs ready for real-time processing in live sound engineering? - Simon Schneider - ADCxGather 2024
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Parallelising real-time audio effects requires complex task management and synchronisation. GPUs are optimised for parallel processing while still retaining flexible scheduling comparable to a CPU. As a result, it combines the strengths of both DSPs and CPUs in a single device. In addition, recent trends advocate using AI audio processing algorithms, which work best on GPU architectures.

This thesis presents an implementation of an embedded GPU-based audio processing framework on an Nvidia Jetson hardware platform. It can combine neural network inference and other audio effects into signal graphs that process within periods as small as 32 frames (0.667ms).

The signal graph does not restrict the number and combination of parallel and serial audio effects as long as the real-time limit is met. Therefore, the framework has been tested on large numbers of parallel channels, as found in a mixing console, and complex routing options available in high-end audio effect processors, such as the Neural DSP Quad Cortex.

Launching GPU work using the CUDA graph API produces better stability and performance than was observed using the CUDA stream API in a 2017 study. Processing a signal graph that fully utilises the Jetson's resources by mimicking a 64-channel mixing console on a 128-frame (2.67ms) period has a higher than 99% success rate. However, occasional stalling on the GPU can produce worst-case execution times of up to 20ms, regardless of the loaded audio effects. As a result, the framework can not yet be classified as real-time capable.
Further study of the CUDA scheduler and improvements to the operating system and audio driver may be able to achieve real-time capability in the future.
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Simon Schneider

Simon is a musician based in Winterthur. After completing his Bachelor's Degree in IT he realized that he could combine his passion for music and software engineering in audio development. As a result, he went on to complete a Master's Degree in Electrical Engineering to learn about signal processing and hardware programming. During this time he was working part-time in the ZHAW Institute of Embedded Systems. There he developed an audio effects processing platform on an Nvidia Jetson GPU as part of his Master Thesis.

His bandmates will say, that playing the guitar is just an excuse to justify all the money he spends on music-related gear. While this is not entirely untrue, Simon is the type of programmer who spends days automating or streamlining a repetitive process that takes minutes to complete manually.
As a result, automating guitar effect changes or building a wireless InEar monitoring rack for shorter live show setup and teardown times simply requires a lot of gear.

Furthermore, Simon has a flair for modular and customizable software architecture. Since audio gear often lacks both of these qualities, he endeavours to make them a primary focus in all his audio development projects.
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ADC is an annual event celebrating all audio development technologies, from music applications and game audio to audio processing and embedded systems. ADC’s mission is to help attendees acquire and develop new audio development skills, and build a network that will support their audio developer career.
Annual ADC Conference - https://audio.dev/
https://www.linkedin.com/company/audiodevcon

https://facebook.com/audiodevcon
https://instagram.com/audiodevcon
https://www.reddit.com/r/audiodevcon/
https://mastodon.social/@audiodevcon
---

Streamed & Edited by Digital Medium Ltd: https://online.digital-medium.co.uk
---

Organized and produced by JUCE: https://juce.com/
---

Special thanks to the ADCxGather Team:

Sophie Carus
Derek Heimlich
Andrew Kirk
Bobby Lombardi
Tom Poole
Ralph Richbourg
Jim Roper
Jonathan Roper
Prashant Mishra

#audioprocessing #gpu #ai #adc #audiodev #dsp #audio #conferenceaudio #audioproduction #audioprogramming #musictech #soundtech #audiotech #audiotechnology

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KEYNOTE: Foundation Models Don’t Understand Me – Lessons From AI Lutherie for Live Performances – Manaswi Mishra

https://audio.dev/ -- @audiodevcon​
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Keynote: Foundation Models Don’t Understand Me - Lessons From AI Lutherie for Live Performances - Manaswi Mishra - ADC 2024
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Living in a world of rapidly accelerating synthetic media, the outputs of generative AI often leave us feeling frustrated, amused, and even manipulated. Early examples of creative AI tools struggle to go beyond imitating styles and patterns, producing a context-less blend of borrowed aesthetics from the datasets they’re trained on. This race to the statistically average flattened aesthetic, misunderstands the core goals of creative expression. In contrast, Audio developers and Instrument builders understand the importance of providing a toolkit of exploration, intentional serendipity and discovery to a new age of artists performing with AI. In my work of building AI musical instruments for live Opera, Symphony and Installations, I share a framework of frustrations and guidelines for AI instrument building.
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Slides: https://data.audio.dev/talks/2024/foundation-models-dont-understand-me/slides.pdf
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Manaswi Mishra

Manaswi Mishra is a LEGO Pappert Fellow and a current PhD research assistant in the Opera of the Future group, MIT Media Lab. His research explores strategies and frameworks for a new age of composing, performing and learning music using A.I. centered on bespoke human intent. He joined the MIT Media Lab in 2019 and completed his MS in Media Arts and Science, developing his work “Living, Singing A.I”, to empower bespoke A.I. music making with just the human voice. His AI instruments have been featured in Opera and Symphony performances like VALIS (2023), Brain Opera (2022), Flow Symphony (2024). His work has been published and exhibited in the MIT Press, Harvard Tech Review, Washington Post, Boston Globe, Conferences of Computational Creativity, ISEA Brisbane, IFA Stuttgart, CVPR 2024, Burning Man 2023, Copyright Society 2023, Bloomberg Law, Seoul Arts Center, etc.

Prior to joining MIT, he did a Masters in Music Technology at UPF, Barcelona and Bachelors in Technology at the Indian Institute of Technology Madras. He is passionate about a creative future where every individual can express, reflect, create and connect through music. Manaswi is also a founding instigator of the Music Tech Community in India and has organized workshops, hackathons and community events to foster a future of music and technology in his home country. In his free time, Manaswi loves collecting weird sounds.
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ADC is an annual event celebrating all audio development technologies, from music applications and game audio to audio processing and embedded systems. ADC’s mission is to help attendees acquire and develop new audio development skills, and build a network that will support their audio developer career.
Annual ADC Conference - https://audio.dev/
https://www.linkedin.com/company/audiodevcon
https://twitter.com/audiodevcon
https://facebook.com/audiodevcon
https://instagram.com/audiodevcon
https://www.reddit.com/r/audiodevcon/
https://mastodon.social/@audiodevcon
---

Streamed & Edited by Digital Medium Ltd: https://online.digital-medium.co.uk
---

Organized and produced by JUCE: https://juce.com/
---

Special thanks to the ADC24 Team:

Sophie Carus
Derek Heimlich
Andrew Kirk
Bobby Lombardi
Tom Poole
Ralph Richbourg
Jim Roper
Jonathan Roper
Prashant Mishra

#ai #artificialintelligence #artificialintelligencetechnology #adc #audiodev #audio #conferenceaudio #audioprocessing #audioproduction #audioprogramming #musictech #soundtech #audiotech #audiotechnology

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Pro Tools Scripting SDK and AI: Driving Workflows & In-App Help – Paul Vercelotti & Sam Butler ADC23

Join Us For ADC24 - Bristol - 11-13 November 2024
More Info: https://audio.dev/
@audiodevcon​

Pro Tools Scripting SDK and AI: Driving Workflows and In-App Help - Paul Vercelotti & Sam Butler - ADC 2023

Last year at ADC, Avid announced a new and free Pro Tools scripting SDK which allows third-party developers to create solutions that tightly integrate with Pro Tools in ways that have not been possible before. Continuing the conversation that started last year, Avid will present at ADC '23 a technical preview that shows how the power of large language models can be combined with the Pro Tools scripting SDK to automate workflows and assist users. In addition, Avid will update the development community on the status of the SDK program.

Link to Slides:
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Paul Vercelotti

Paul Vercellotti is a software architect at Avid Audio and the technical / architectural lead for Pro Tools. He focuses on architectural design direction for current and future Avid Audio products and technical leadership for the Avid Audio engineering team. He has been creating audio software for over 25 years and is passionate about solving the fun and challenging problems of audio and music.
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Sam Butler

Sam has worked at Avid for over 20 years, starting off in technical support for Sibelius, running public demos, putting sound libraries together for the Sibelius Sounds libraries, then moving to product management in 2013. In the past decade, Sam has product managed projects to put Avid solutions into the cloud and on mobile, helped spearhead the modernisation of our infrastructure and kept the features rolling. Now Director of Product Management for Sibelius and the Audio SDKs, Sam works with all the departments in Avid to produce the future of the audio products and solutions.
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Streamed & Edited by Digital Medium Ltd: https://online.digital-medium.co.uk
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Organized and produced by JUCE: https://juce.com/
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Special thanks to the ADC23 Team:

Sophie Carus
Derek Heimlich
Andrew Kirk
Bobby Lombardi
Tom Poole
Ralph Richbourg
Jim Roper
Jonathan Roper
Prashant Mishra

#adc #ai #dsp #audio #protools

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Deep Learning for DSP Engineers: Challenges & Tricks for Audio AI – Franco Caspe & Andrea Martelloni

https://audio.dev/ -- @audiodevcon​

Deep Learning for DSP Engineers: Challenges and Tricks for Audio AI - Franco Caspe & Andrea Martelloni - ADC23

This talk aims to tackle and demystify the process of the development of an AI-based musical instrument, audio tool or effect. We want to view this process not from the point of view of technical frameworks and technical challenges, but from that of the design process, the knowledge required and the learning curve needed to be productive with AI tools; particularly if one approaches AI from an audio DSP background, which was our situation when we started out.

We are going to quickly survey the current applications of AI for real-time music making, and reflect on the challenges that we found, especially with current learning resources. We will then walk through the process of developing a real-time audio model based on deep learning, from dataset to deployment, highlighting the relevant aspects for those with a DSP background. Finally, we will describe how we applied that process to our own PhD projects, the HITar and the Bessel’s Trick.

Link to Slides:
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Franco Caspe

I’m an electronic engineer, a maker, hobbyist musician and a PhD Student at the Artificial Intelligence and Music CDT at Queen Mary University of London. I have experience in development of real-time systems for applications such as communication, neural network inference, and DSP. I play guitar and I love sound design, so in my PhD I set out to find ways to bridge the gap that separates acoustic instruments and synthesizers, using AI as an analysis tool for capturing performance features present in the instruments’ audio, and as a generation tool for synthetic sound rendering.
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Andrea Martelloni

Inventor of the HITar. Interested in applications of deep learning for rich real-time musical interaction and expressive digital musical instruments.
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Streamed & Edited by Digital Medium Ltd: https://online.digital-medium.co.uk
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Organized and produced by JUCE: https://juce.com/
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Special thanks to the ADC23 Team:

Sophie Carus
Derek Heimlich
Andrew Kirk
Bobby Lombardi
Tom Poole
Ralph Richbourg
Jim Roper
Jonathan Roper
Prashant Mishra

#adc #dsp #audio #ai #deeplearning

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Inference Engines and Audio – Harriet Drury – ADC23

https://audio.dev/ -- @audiodevcon​

Inference Engines and Audio - Harriet Drury - ADC 2023

Machine learning has become a buzzword in recent years, but how does it actually work? This talk aims to introduce and explain inference pipelines. We’ll look at commonly used inference engines, how they work, their suitability for use in audio applications, and how to go about creating your own.

Also introduced will be an approach to writing a custom inference engine for the Cmajor platform.

Link to Slides: https://data.audio.dev/talks/2023/inference-engines-and-audio/slides.pdf
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Harriet Drury
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Streamed & Edited by Digital Medium Ltd: https://online.digital-medium.co.uk
_

Organized and produced by JUCE: https://juce.com/
_

Special thanks to the ADC23 Team:

Sophie Carus
Derek Heimlich
Andrew Kirk
Bobby Lombardi
Tom Poole
Ralph Richbourg
Jim Roper
Jonathan Roper
Prashant Mishra

#adc #audio #audiotech #machinelearning

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