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Abstract
The ratio spectrum is a novel spectral representation that has shown promise for improved speech compression, coding, feature extraction and recognition. In effect, the ratio spectrum combines the standard front-end filter bank with a feature extraction process to produce a model that requires dramatically less hardware (or software). Alternatively, the model can be viewed as a small set of constant-Q filters whose center frequencies adapt to locations of high signal energy. The resulting feature vectors are shown to outperform several competing techniques for phoneme recognition (e.g. LPC and cepstrum). We also have implemented speech and audio coding using the ratio spectrum and standard spectrum inversion techniques. Finally, results from fabricated CMOS analog VLSI circuits illustrate a hardware efficient method to sample the ratio spectrum, paving the way for ultra low-power front-end speech processing and feature extraction.
Biography
Dr. John G. Harris earned his BS and MS degrees in Electrical Engineering from MIT in 1983 and 1986 where he studied massively parallel vision algorithms. He then worked for one year at the Hughes Research Labs in Malibu, CA implementing perception algorithms for the DARPA Autonomous Land Vehicle. In 1987, Dr. Harris joined the interdisciplinary Computation and Neural Systems Program at Caltech. He earned his PhD in 1991 from Caltech developing novel silicon vision systems. After a two-year post doc at the MIT Artificial Intelligence Lab, Dr. Harris joined the faculty of the University of Florida in 1993 where he is currently an Associate Professor in Electrical and Computer Engineering. Dr. Harris leads the UF Analog Computation Group in researching biologically-inspired signal processing and analog VLSI sensory processing. He is the recipient of an NSF CAREER Award as well as a UF Teaching Improvement Program award.