English Speech Recognition System on Chip  

作　　者：刘鸿 钱彦旻 刘加 

机构地区：[1]Tsinghua National Laboratory for Information Science and Technology,Department of Electronic Engineering,Tsinghua University

出　　处：《Tsinghua Science and Technology》2011年第1期95-99,共5页清华大学学报（自然科学版（英文版）

基　　金：Supported by the National Natural Science Foundation of China and Microsoft Research Asia(No. 60776800);the National Natural Science Foundation of China and Research Grants Council (No.60931160443);the National High-Tech Research and Development (863) Program of China(Nos. 2006AA010101,2007AA04Z223,2008AA02Z414,and 2008AA040201)

摘　　要：An English speech recognition system was implemented on a chip, called speech system-on-chip （SoC）. The SoC included an application specific integrated circuit with a vector accelerator to improve performance. The sub-word model based on a continuous density hidden Markov model recognition algorithm ran on a very cheap speech chip. The algorithm was a two-stage fixed-width beam-search baseline system with a variable beam-width pruning strategy and a frame-synchronous word-level pruning strategy to significantly reduce the recognition time. Tests show that this method reduces the recognition time nearly 6 fold and the memory size nearly 2 fold compared to the original system, with less than 1% accuracy degradation for a 600 word recognition task and recognition accuracy rate of about 98%.An English speech recognition system was implemented on a chip, called speech system-on-chip （SoC）. The SoC included an application specific integrated circuit with a vector accelerator to improve performance. The sub-word model based on a continuous density hidden Markov model recognition algorithm ran on a very cheap speech chip. The algorithm was a two-stage fixed-width beam-search baseline system with a variable beam-width pruning strategy and a frame-synchronous word-level pruning strategy to significantly reduce the recognition time. Tests show that this method reduces the recognition time nearly 6 fold and the memory size nearly 2 fold compared to the original system, with less than 1% accuracy degradation for a 600 word recognition task and recognition accuracy rate of about 98%.

关 键 词：non-specific human voice-consciousness SYSTEM-ON-CHIP mel-frequency cepstral coefficients （MFCC） 

分 类 号：TN912.34[电子电信—通信与信息系统] TN402[电子电信—信息与通信工程]