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To contact us regarding investment, licensing or partnering:
President, Circular Logic
Boca Raton FL, USA
Contact via email
Interactive audio technologies depend on signal processing algorithms to process sound. These technologies enable interaction between people and computer systems, and are core components leading to next generation audio devices such as music systems, auditory prostheses, and speech recognition systems. Circular Logic's patented technology enables nonlinear signal processing to be effectively and efficiently implemented in digital hardware or software.
The company is building its core business in the computer music market, with 2.7 million users for our technologies. We plan to subsequently target the hearing aid and cochlear implant markets with 700 million potential users, and the speech technology market which reaches most everyone using a communications technology. We will produce consumer software products in the computer music market. We plan to license our technology in the hearing aid, cochlear implant and other markets, and we seek licensees to integrate our technology into end-user products, and strategic partners to collaborate in end-use product development.
Current generation audio technologies don't work as well as they should. The problem is that state-of-the-art audio signal processing technologies employ linear systems almost exclusively, approximating human auditory capabilities only roughly. Next-generation signal processing algorithms must mimic the remarkable capabilities of human auditory perception, capabilities that arise from nonlinear processes in the auditory system. If signal processing algorithms were able to mimic these capabilities, many limitations of audio technologies would disappear.
No existing technology can duplicate the perceptual feats that are accomplished routinely by the human auditory system. Humans can detect impossibly faint sounds and identify minuscule differences in frequency, timing and intensity. Even more impressively, we can recognize complex acoustic patterns under challenging listening conditions, such as in a crowded room or on a city street. We can learn to recognize new patterns that are significant to us, such as a new friend’s voice or the sound of an airplane. We can segregate sounds from one another in natural environments, to attend to one event while filtering out the others.
Imagine a technology that could perform such feats automatically, or could help restore such capabilities in humans who lose all or part of their hearing. This technology could be used to automatically detect, recognize and understand a human voice in a crowded room. It could identify and transcribe individual instruments in a jazz quartet. It could be used to reestablish normal function in a damaged human auditory system.
We are developing such a technology.
Advantages and Differentiating Features
Current signal processing technologies employ linear systems almost exclusively, and they approximate human perceptual capabilities only roughly. However, recent research suggests that nonlinear processes like cochlear outer hair cells and auditory neurons respond to multiple related frequencies through nonlinear resonance, in a manner that is fundamentally different from linear techniques such as Fourier analysis.
Our novel technology simulates auditory nonlinearities, achieving signal processing, pattern analysis, and learning using neural networks that resonate to acoustic signals. It is able to perform these feats in the presence of noise and alternative target signals.
Applications & Benefits
Our technology will power the next generation of interactive audio applications. Music performance systems will be able to follow the tempo of complex rhythms. Music transcription systems will be able to identify individual instruments and notes within ensemble recordings. Hearing aid wearers will be better able to understand speech in a noisy room. Cochlear implant users will experience drastically improved sound quality. Speech transcription systems will function even amidst background noise.