Center for Computer Research in Music and Acoustics
Upcoming Events
Nat Condit-Schultz on Tempo, Tactus, Rhythm, Flow: Computational Hip Hop Musicology in Theory and Practice
Concepts and Control: Understanding Creativity in Deep Music Generation
Abstract: Recently, generative AI has achieved impressive results in music generation. Yet, the challenge remains: how can these models be meaningfully applied in real-world music creation, for both professional and amateur musicians? We argue that what’s missing is an interpretable generative architecture—one that captures music concepts and their relations, which can be so finely nuanced that they defy straightforward description. In this talk, I will explore various approaches to creating such an architecture, demonstrating how it enhances control and interaction in music generation.
Juhan Nam, "My Journey Toward Musically Intelligent Machines"
Creating intelligent machines that can listen to, play, and even making music has been a longstanding human ambition. Recent advancements in AI, especially through deep learning, have brought us closer to realizing this vision. In this talk, I will share my personal journey in developing musically intelligent machines, beginning with my PhD research on music representation learning during the early days of deep learning, and continuing with my collaborative work with students over the past decade at KAIST. Key topics will include bridging music audio with language, human-AI music ensemble performances, and neural audio processing.
Bio
Tristan Peng's Piano Recital
Recital Program
- Prokofiev Piano Sonata No. 3, Op. 28
- Bach Toccata in E Minor, BWV 914
- Chopin Nocturnes Op. 48
- Ravel Miroirs
Foreign/Domestic
FREE and Open to the Public | In Person + Livestream
Recent Events
The New Sound of New Music: Contemporary Composition and Modern Record Production Practices, two part lecture series with Murat Çolak
Homage to Ligeti | CCRMA 50th Anniversary
FREE and Open to the Public | In Person + Livestream
Distractfold x Graduate Composers
Works by: Celeste Betancur, Seán Ó Dálaigh, Mohammad H. Javaheri, Lemon Guo, Kimia Koochakzadeh-Yazdi, Calvin Van Zytveld, Mercedes Montemayor Elosua
Gerald Schuller: Perceptual and higher-level loss and distance functions for machine learning in audio and acoustics
Prof. Gerald Schuller will report on the potential transformative role of perceptual loss functions and distance metrics in enhancing audio and acoustic machine learning models, and their applications. He will cover theoretical foundations of perceptual loss functions, which mimic human auditory perception, and also more abstract, higher-level representations, and explore how these functions, along with novel distance metrics, significantly improve the performance of audio processing tasks. Applications involving loss functions for room impulse responses, audio similarity, and audio representations for cochlear implants will be discussed.
Prof. Marina Bosi will be hosting his visit.
Join us in Zoom if you cannot make it in person!
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