An analog VLSI vocal tract
Author(s)
Wee, Keng Hoong
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Alternative title
Analog very large scale integration vocal tract
Other Contributors
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Advisor
Rahul Sarpeshkar.
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Increasingly, circuit models of biology are being used to improve performance in engineering systems. For example, silicon-cochlea-like models have led to improved speech recognition in noise and low-power cochlear-implant processors for the deaf. A promising approach to improve the naturalness of synthetic speech is to exploit bioinspired models of speech production with low bit-rate control parameters. In this work, we present the first experimental integrated-circuit vocal tract by mapping fluid volume velocity to current, fluid pressure to voltage, and linear and nonlinear mechanical impedances to linear and nonlinear electrical impedances. The 275 jW analog vocal tract chip can be used with auditory processors in a feedback speech locked loop to implement speech recognition that is potentially robust in noise. Our use of a physiological model of the human vocal tract enables the analog vocal tract chip to synthesize speech signals of interest, using articulatory parameters that are intrinsically compact and linearly interpolatable. Previous attempts that take advantage of the powerful analysis-by-synthesis method employed computationally expensive approaches to articulatory synthesis using digital computation. Our strategy uses an analog vocal tract to drastically reduce power consumption, enables real-time performance and could be useful in portable speech processing systems of moderate complexity, e.g., in cell phones, digital assistants and bionic speech-prosthesis systems.
Description
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008. Includes bibliographical references (p. 165-168).
Date issued
2008Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.