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Audio Modeling & GPU Audio Partner to Accelerate SWAM Product Line


Audio Modeling and GPU Audio have announced a partnership aimed at enhancing the capabilities of Audio Modeling's SWAM (Synchronous Waves Acoustic Modeling) product line through the integration of GPU technology. This collaboration focuses on improving the performance of existing products and developing new virtual instruments.

Our partnership with GPU Audio represents a colossal leap forward in the realm of virtual instruments. By merging our expertise with the cutting-edge technology of GPU Audio, we aren't merely pushing the envelope but shattering the boundaries of what music technology can achieve. The increased computational power will enable us to surpass the existing limits of technology, fostering the development of even more lifelike instruments. In the world of physical modeling, the possibilities are boundless, and we believe we are only at the beginning of something truly extraordinary.

Simone Capitani, Partner at Audio Modeling

Bill Collins, Head of Product and Partnerships at GPU Audio, shared similar sentiments, noting:

We've discovered like-minded collaborators with Audio Modeling, who are actively exploring the frontiers of music technology. Together, we share a common goal: to provide composers and producers with cutting-edge music production tools. This goal will come to fruition as we integrate our accelerated audio processing capabilities with their next-generation SWAM (Synchronous Waves Acoustic Modeling) product line.

The SWAM engine, a core technology of Audio Modeling, is designed to transcend traditional sampler limitations by combining Physical and Behavioral Modeling with Multi-Vector/Phase-Synchronous Sample-Morphing techniques. It is available in three versions: SWAM-B, SWAM-W, and SWAM-S, catering to Brass, Woodwinds, and Bowed Strings, respectively.

For additional information on the technologies and products offered by GPU Audio and Audio Modeling, visit their respective websites:

YouTube.com/watch?v=knf_EELbBWg

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