Head of Music AI, Adobe Research (personal account)

Joined April 2010
4 Photos and videos
Pinned Tweet
Introducing #AIStudio via #AdobeStock — edit stock assets before licensing stock.adobe.com/ai-studio AI Studio features #AudioMatch -- create custom soundtracks for video before licensing. Proud of the #team 🥂👇 Adobe Stock's new economic models to blend #GenAI w/licensing.
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Excited for "Beats" is released in @Adobe #PremiereMobile on iOS! We detect musically meaningful markers within your music to sync, snap, and cut to your video. Three visualization options corresponding to less → more markers. w/@JojoGiltsoff, Eric Brandt, @j_p_caceres !
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🎶 V2M-Zero: SOTA time-sync'd video-to-music! 🎶 * Music sync'd to dance, scene cuts, * Easily adapt existing TTM models, * No paired video-music data, * SOTA objective human preference. Exceptional work @yblin98 @casebeer! w/@mtlong_88 @aniruddha26398 @gberta227, me
🎵🎵What if we could generate video soundtracks without paired video–music data? Introducing V2M-Zero, a method that generates music synchronized with video events. arxiv.org/abs/2603.11042 w. @CasebeerJonah @mtlong_88 @aniruddha26398 @gberta227 @NicholasJBryan
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Audio VAEs VQ-VAEs designed for #GenAI! * Ultra-fast encoding for on-the-fly training pipelines, * ~2x more compression (13Hz) w/frontier quality, * Any format (mono, stereo LR, MS, mel, raw), * Cont. or discrete latents. 👏 @CasebeerJonah! w/@__gzhu__ @zhepeiw03, me
GenAE: An audio autoencoder engineered for generative modeling. To appear at ICASSP 2026. w/ @__gzhu__ @zhepeiw03 @NicholasJBryan arXiv: arxiv.org/abs/2602.15749 Video: youtu.be/gDIIuLb0cf0
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TAC: Timestamped Audio Captioning 👇
This is big. SOTA audio reasoning. SOTA video reasoning. SOTA audio captioning. SOTA sound event detection. Better than Gemini. Better than Qwen. TAC: Timestamped Audio Captioning 📑 paper: lnkd.in/getEz5xU 🌐 website with more demos: lnkd.in/gdw5TTuS
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Thrilled about Stemphonic! All-at-once Flexible Multi-stem Music Generation! w/@slseanwu @__gzhu__ @j_p_caceres @huangcza and myself
Excited to announce our ICASSP 2026 paper "Stemphonic: All-at-once Flexible Multi-stem Music Generation" ! w/ @__gzhu__, @j_p_caceres, @huangcza, and @NicholasJBryan 🔊Demo stemphonic-demo.vercel.app 📰Paper arxiv.org/abs/2602.09891 More details in🧵
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Nicholas J. Bryan retweeted
Replying to @LudovicCreator
I've been playing with Generate Soundtrack a lot today. It is pretty great, and really fast. I've been collecting a bunch of alternate music options from my videos.
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Nicholas J. Bryan retweeted
Why no one is talking about the new Meta AI - Image and Video generation which is partnered with Midjourney and Black Forest Labs?? The generations are fascinating. Image and Video generated with @Meta @AIatMeta Music - @Adobe Generate Soundtrack @alexandr_wang #MetaAI
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Nicholas J. Bryan retweeted
Replying to @dreamina_ai
Added sound in @AdobeFirefly , generate soundtrack feature
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Nicholas J. Bryan retweeted
Thrilled to announce “MIDI-LLM: Adapting LLMs for Text-to-MIDI Music Generation” w/ @huangcza and Yoon Kim! 🎸 Live Demo midi-llm-demo.vercel.app 💻 github.com/slSeanWU/MIDI-LLM 🤗 huggingface.co/slseanwu/MIDI… From a text prompt, it generates MIDIs you can edit directly in a DAW 🧵
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Congrats @JCJesseLai and Team!
Tired to go back to the original papers again and again? Our monograph: a systematic and fundamental recipe you can rely on! 📘 We’re excited to release 《The Principles of Diffusion Models》— with @DrYangSong, @gimdong58085414, @mittu1204, and @StefanoErmon. It traces the core ideas that shaped diffusion modeling and explains how today’s models work, why they work, and where they’re heading. 🧵You’ll find the link and a few highlights in the thread. We’d love to hear your thoughts and join some discussions! ⚡ Stay tuned for our markdown version, where you can drop your comments!
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Nicholas J. Bryan retweeted
28 Oct 2025
Adobe’s new AI audio tools can add soundtracks and voice-overs to videos theverge.com/news/807809/ado…
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Adobe's #GenerateSoundtrack is LIVE today! 🎉 Studio-quality music for storytellers🎵 * Trained on #Licensed data, * Commercially safe, royalty-free, and cleared for any use, & * Exported with #ContentCredentials for transparency and attribution. Get started: firefly.adobe.com/generate/s… Powered by the #FireflyAudioModel, and built by an incredible R&D team: @j_p_caceres @CasebeerJonah @__gzhu__ @zhepeiw03 @ailiefraser @NicholasJBryan Excited for the Team. Much more to come! #Adobe #AdobeMAX #GenerateSoundtrack #FireflyAudioModel
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Nicholas J. Bryan retweeted
22 Apr 2025
Adobe announced DRAGON on Hugging Face Distributional Rewards Optimize Diffusion Generative Models
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Introducing "DRAGON: Distributional Rewards Optimize Diffusion Generative Models"! 📖: arxiv.org/abs/2504.15217 🎹: ml-dragon.github.io/web/ A new framework for fine-tuning gen models towards a target distribution. By Yatong Bai w/@CasebeerJonah @somayeh_sojoudi @NicholasJBryan
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With an appropriate exemplar set, DRAGON achieves a 60.95% human-voted music quality win rate without training on human preference annotations.
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DRAGON introduces a new approach to designing and optimizing reward functions to enhance human-perceived quality.
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