Proceedings of the 1st IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
A low-power accelerator for the SPHINX 3 speech recognition system
Proceedings of the 2003 international conference on Compilers, architecture and synthesis for embedded systems
Architectural optimizations for low-power, real-time speech recognition
Proceedings of the 2003 international conference on Compilers, architecture and synthesis for embedded systems
Memory system design space exploration for low-power, real-time speech recognition
Proceedings of the 2nd IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Parallelization and analysis of speech recognition on mobile multi-core processor
CCNC'09 Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference
Fast Likelihood Computation in Speech Recognition using Matrices
Journal of Signal Processing Systems
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In this paper we describe and characterize the speech recognition process, and assess the suitability of current microprocessors and memory systems for running speech recognition applications. We use representative benchmark applications-RASTA to characterize the signal-processing on the front end, and SPHINX for the graph search on the back end Recognition time is dominated by the back end, which substantially exercises the memory system and exhibits low levels of instruction-level parallelism (ILP). As a result, SPHINX yields an average instructions per cycle (IPC) of 0.64 on a simulated 4-issue out-of-order microprocessor We identify intelligent layout and thread-level parallelization as the primary methods to improve throughput, showing tipper bounds on the performance improvements that these methods can achieve.