DocumentCode :
727179
Title :
A 3.13nJ/sample energy-efficient speech extraction processor for robust speech recognition in mobile head-mounted display systems
Author :
Jinmook Lee ; Seongwook Park ; Injoon Hong ; Hoi-Jun Yoo
Author_Institution :
Dept. of Electr. Eng., KAIST, Daejeon, South Korea
fYear :
2015
fDate :
24-27 May 2015
Firstpage :
1790
Lastpage :
1793
Abstract :
An energy-efficient speech extraction (SE) processor is proposed for the robust speech recognition in the head-mounted display (HMD) systems. Speech extraction is essential for robust speech recognition in noisy environment. For the low-latency speech extraction, FastSE is proposed to overcome 50x larger complex cICA-based selection process which results in <;2ms SE latency. Moreover, a reinforced-FastSE (RFSE) scheme is proposed to achieve 97.2% accuracy with small on-chip memory size of only 33kB for the low-power HMD applications. Also, Reconfigurable matrix operation accelerator (RMAT) is implemented for energy-efficient acceleration of dominant matrix operation on SE. As a result, the proposed SE processor achieves 1.3x lower latency with 4.24x smaller memory compared to the state-of-the-art work, so that speech recognition in noisy environment becomes possible for mobile HMD applications.
Keywords :
helmet mounted displays; independent component analysis; speech recognition; FastSE; RMAT; SE processor; complex cICA-based selection process; energy-efficient speech extraction processor; mobile HMD applications; mobile head-mounted display systems; reconfigurable matrix operation accelerator; reinforced-FastSE scheme; robust speech recognition; Accuracy; Energy efficiency; Integrated circuits; Robustness; Speech; Speech processing; Speech recognition; Head-Mounted Display Systems; Reconfigurable Architecture; Speech extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems (ISCAS), 2015 IEEE International Symposium on
Conference_Location :
Lisbon
Type :
conf
DOI :
10.1109/ISCAS.2015.7169002
Filename :
7169002
Link To Document :
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