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LIS-Net: An end-to-end light interior search network for speech command recognition

机译：LIS-NET：用于语音命令识别的端到端灯室内搜索网络

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摘要

With the rapid development of deep learning techniques, speech-based communication is getting more practically to be embedded into smart devices such as Alexa echo, TV, Fridge, etc. In this work, we have developed an efficient yet accurate Speech Command Recognition (SCR), that is particularly appropriate for low-resource devices. To this aim, a novel neural network, called Light Interior Search Network (LIS-Net). is presented that works with raw speech signal. LIS-Net is structurally composed of a sequence of parameterized LIS-Blocks, each of which is a stack of LIS-Cores, exploring the feature-map inheritance to learn highly distinctive and lightweight footprint of speech patterns. The proposed network is validated on Google Speech Commands benchmark speech datasets, demonstrating a significant improvement of accuracy and processing time in comparison with other state-of-the-art techniques.
机译：随着深度学习技术的快速发展，基于语音的沟通正在更实际地嵌入到智能设备中，例如Alexa Echo，TV，冰箱等。在这项工作中，我们开发了一种有效但准确的语音命令识别（SCR ），这是特别适用于低资源设备。为此目的是一种新型神经网络，称为光内部搜索网络（LIS-NET）。介绍了使用原始语音信号的工作。 LIS-NET由一系列参数化的LIS块组成，每个参数化LIS-块是LIS-CORE的堆栈，探索了特征映射继承，以学习语音模式的高度独特和轻质的占地面积。所提出的网络在Google语音命令基准语音数据集上验证，展示了与其他最先进的技术相比的准确性和处理时间的显着提高。

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  • 来源
    《Computer speech and language》 |2021年第1期|101131.1-101131.14|共14页
  • 作者

    Nguyen Tuan Anh; Yongjian Hu; Qianhua He; Tran Thi Ngoc Linh; Hoang Thi Kim Dung; Chen Guang;

  • 作者单位

    School of Electronic and Information Engineering South China University of Technology Guangzhou 510641 PR China;

    School of Electronic and Information Engineering South China University of Technology Guangzhou 510641 PR China;

    School of Electronic and Information Engineering South China University of Technology Guangzhou 510641 PR China;

    Faculty of Electronic Engineering Thai Nguyen University of Technology Thai Nguyen Vietnam;

    Faculty of Civil and Environment Thai nguyen University of Technology Thai Nguyen Vietnam;

    R&D Department 9-11 Kelin road. High-tech Industrial Development Zone Guangzhou 510640 PR China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Deep neural network; Speech Command Recognition; SCR; Keyword spotting; KWS; Light Interior Search Network; LIS-Net;

    机译：深神经网络;语音命令识别;SCR;关键词斑点;kws;光内部搜索网络;丽峰;

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