New silicon audition papers online ...

John Lazzaro lazzaro at CS.Berkeley.EDU
Mon Jan 13 19:13:02 EST 1997



	Two new papers on silicon audition available online ... 

							--john lazzaro



			 (presented at NIPS*96)

			A Micropower Analog VLSI
		   HMM State Decoder for Wordspotting

		     John Lazzaro and John Wawrzynek
			CS Division, UC Berkeley

			    Richard Lippmann
			 MIT Lincoln Laboratory


			       ABSTRACT

We describe the implementation of a hidden Markov model state decoding
system, a component for a wordspotting speech recognition system.  The
key specification for this state decoder design is microwatt power
dissipation; this requirement led to a continuous-time, analog circuit
implementation. We describe the tradeoffs inherent in the choice of an
analog design and explain the mapping of the discrete-time state
decoding algorithm into the continuous domain. We characterize the
operation of a 10-word (81 state) state decoder test chip.


Available on the Web at:

http://http.cs.berkeley.edu/~lazzaro/biblio/decoder.ps.gz





	           (forthcoming UCB Technical Report)

		Anawake: Signal-Based Power Management
		For Digital Signal Processing Systems

		     John Lazzaro and John Wawrzynek
			CS Division, UC Berkeley

			    Richard Lippmann
			 MIT Lincoln Laboratory


			       ABSTRACT

Single-chip, low-power, programmable digital signal processing systems
are capable of hosting complete speech processing applications, while
consuming a few milliwatts of average power. We present a power
management architecture that decreases the average power consumption
of these systems to 3--10 microwatts, in applications where speech
signals are present with a sufficiently low duty cycle. In this
architecture, a micropower analog signal processing system, {\it
Anawake,} continuously analyzes the incoming signal, and controls the
power consumption of the DSP system in a signal-dependent way. We
estimate system power consumption for Anawake designs optimized for
different peak-speech-signal to average-background-noise ratios.


Available on the Web at:

http://http.cs.berkeley.edu/~lazzaro/biblio/anawake.ps.gz







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