A low-power integrated circuit for remote speech recognition

被引:1
|
作者
Borgatti, M [1 ]
Felici, M [1 ]
Ferrari, A [1 ]
Guerrieri, R [1 ]
机构
[1] Univ Bologna, DEIS, I-40136 Bologna, Italy
关键词
CMOS digital integrated circuits; digital signal processors; low-power circuits; low-voltage circuits; speech analysis; speech recognition;
D O I
10.1109/4.701266
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, a low-power, low-voltage speech processing system is presented. The system is intended to be used in remote speech recognition applications where feature extraction is performed on terminal and high-complexity recognition tasks are moved to a remote server accessed through a radio link. The proposed system is based on a CMOS feature extraction chip for speech recognition that computes 15 cepstrum parameters, each 8 ms, and dissipates 30 mu W at 0.9-V supply. Single-cell battery operation is achieved. Processing relies on a novel feature extraction algorithm using 1-bit A/D conversion of the input speech signal. The chip has been implemented as a gate array in a standard 0.5-mu m, three-metal CMOS technology. The average energy required to process a single word of the TI46 speech corpus is 10 mu J. It achieves recognition rates over 98% in isolated-word speech recognition tasks.
引用
收藏
页码:1082 / 1089
页数:8
相关论文
共 50 条
  • [21] Low-power Design of Digital Integrated Circuit Based on UPF Standard
    Lu, Yuncheng
    PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON INFORMATION ENGINEERING FOR MECHANICS AND MATERIALS, 2016, 97 : 108 - 112
  • [22] Local field potential measurement with low-power analog integrated circuit
    Harrison, RR
    Santhanam, G
    Shenoy, KV
    PROCEEDINGS OF THE 26TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7, 2004, 26 : 4067 - 4070
  • [23] Recognition in a low-power environment
    Hammell, J
    Weimerskirch, A
    Girao, J
    Westhoff, D
    25TH IEEE INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS WORKSHOPS, PROCEEDINGS, 2005, : 933 - 938
  • [24] Low-power image recognition
    Yung-Hsiang Lu
    Nature Machine Intelligence, 2019, 1 : 199 - 199
  • [25] Low-power image recognition
    Lu, Yung-Hsiang
    NATURE MACHINE INTELLIGENCE, 2019, 1 (04) : 199 - 199
  • [26] FPGA-based Low-power Speech Recognition with Recurrent Neural Networks
    Lee, Minjae
    Hwang, Kyuyeon
    Park, Jinhwan
    Choi, Sungwook
    Shin, Sungho
    Sung, Wonyong
    2016 IEEE INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING SYSTEMS (SIPS), 2016, : 230 - 235
  • [27] Low-Power Neuromorphic Speech Recognition Engine with Coarse-Grain Sparsity
    Yin, Shihui
    Kadetotad, Deepak
    Yan, Bonan
    Song, Chang
    Chen, Yiran
    Chakrabarti, Chaitali
    Sco, Jea-sun
    2017 22ND ASIA AND SOUTH PACIFIC DESIGN AUTOMATION CONFERENCE (ASP-DAC), 2017, : 111 - 114
  • [28] Low-Power Photoplethysmogram Acquisition Integrated Circuit with Robust Light Interference Compensation
    Kim, Jongpal
    Kim, Jihoon
    Ko, Hyoungho
    SENSORS, 2016, 16 (01):
  • [29] A low-power integrated circuit for adaptive detection of action potentials in noisy signals
    Harrison, RR
    PROCEEDINGS OF THE 25TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4: A NEW BEGINNING FOR HUMAN HEALTH, 2003, 25 : 3325 - 3328
  • [30] A low-power CMOS VLSI circuit for signal conditioning in integrated capacitive sensors
    Dimitropoulos, PD
    Nikolaidis, SP
    Karampatzakis, DP
    Stamoulis, GI
    PROCEEDINGS OF THE IEEE SENSORS 2004, VOLS 1-3, 2004, : 202 - 205