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Sign Languages Recognition Based on Neural Network Architecture

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Intelligent Interactive Multimedia Systems and Services 2017 (KES-IIMSS-18 2018)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 76))

Abstract

In the last years, many steps forward have been made in speech and natural languages recognition and were developed many virtual assistants such as Apple’s Siri, Google Now and Microsoft Cortana. Unfortunately, not everyone can use voice to communicate to other people and digital devices. Our system is a first step for extending the possibility of using virtual assistants to speech impaired people by providing an artificial sign languages recognition based on neural network architecture.

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Notes

  1. 1.

    American Sign Language Image Dataset: http://vlm1.uta.edu/%7Esrujana/ASLID/ASL_Image_Dataset.html.

  2. 2.

    Kinect for Windows SDK 2.0: https://www.microsoft.com/en-us/download/details.aspx?id=44561.

  3. 3.

    MSDN Library - “Coordinate mapping”: https://msdn.microsoft.com/it-it/library/dn785530.aspx.

  4. 4.

    Official Keras documentation: https://keras.io/.

  5. 5.

    HandSpeak ASL Dictionary: http://www.handspeak.com/word/.

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Author information

Authors and Affiliations

  1. Italian National Research Council of Italy, ICAR-CNR, Palermo, Italy

    Filippo Vella, Ignazio Infantino & Salvatore Gaglio

  2. DIID, University of Palermo, Palermo, Italy

    Manuele Palmeri & Salvatore Gaglio

Authors
  1. Manuele Palmeri
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  2. Filippo Vella
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  3. Ignazio Infantino
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  4. Salvatore Gaglio
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Corresponding author

Correspondence to Manuele Palmeri .

Editor information

Editors and Affiliations

  1. National Research Council of Italy (CNR-ICAR), Institute for High-Performance Computing and Networking, Naples, Italy

    Giuseppe De Pietro

  2. National Research Council of Italy (CNR-ICAR), Institute for High-Performance Computing and Networking, Naples, Italy

    Luigi Gallo

  3. Fern Barrow, Bournemouth University, Poole, Dorset, United Kingdom

    Robert J. Howlett

  4. University of Canberra, Canberra, Aust Capital Terr, Australia

    Lakhmi C. Jain

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Palmeri, M., Vella, F., Infantino, I., Gaglio, S. (2018). Sign Languages Recognition Based on Neural Network Architecture. In: De Pietro, G., Gallo, L., Howlett, R., Jain, L. (eds) Intelligent Interactive Multimedia Systems and Services 2017. KES-IIMSS-18 2018. Smart Innovation, Systems and Technologies, vol 76. Springer, Cham. https://doi.org/10.1007/978-3-319-59480-4_12

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  • DOI: https://doi.org/10.1007/978-3-319-59480-4_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59479-8

  • Online ISBN: 978-3-319-59480-4

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