Analog speech recognition project

The Analog Speech Recognition project combines low-power analog signal processing and digital signal processing theory to provide low-power and robust speech processing systems. This project looks to bring together multiple analog signal processing (ASP) blocks into one large ASP system. These component blocks include an analog cepstrum. vector quantizer, and analog HMM. Finally. there are power dissipation comparisons made between the analog and digital systems based on the computations performed.

[1]  John Lazzaro,et al.  Winner-Take-All Networks of O(N) Complexity , 1988, NIPS.

[2]  Paul E. Hasler,et al.  Accurate programming of analog floating-gate arrays , 2002, 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353).

[3]  Christof Koch,et al.  An Adaptive WTA using Floating Gate Technology , 1996, NIPS.

[4]  T. Delbruck 'Bump' circuits for computing similarity and dissimilarity of analog voltages , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

[5]  Jürgen Schürmann,et al.  Pattern classification , 1996 .

[6]  David V. Anderson,et al.  Mel-frequency cepstrum encoding in analog floating-gate circuitry , 2002, 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353).

[7]  G. McLachlan,et al.  Pattern Classification: A Unified View of Statistical and Neural Approaches. , 1998 .

[8]  Jürgen Schürmann,et al.  Pattern classification , 2008 .

[9]  Paul Hasler,et al.  A programmable continuous-time floating-gate Fourier processor , 2001 .