Multi-channel Convolutional Neural Networks for Automatic Detection of Speech Deficits in Cochlear Implant Users

Arias Vergara T, Vasquez Correa J, Gollwitzer S, Orozco-Arroyave JR, Schuster M, Nöth E (2019)

Publication Type: Book chapter / Article in edited volumes

Publication year: 2019

Journal

Lecture Notes in Computer Science Springer Verlag

Edited Volumes: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Series: Image Processing, Computer Vision, Pattern Recognition, and Graphics

Book Volume: 11896

Pages Range: 679-687

ISBN: 9783030339036

DOI: 10.1007/978-3-030-33904-3_64

Authors with CRIS profile

Tomás Arias Vergara Professur für Informatik (Mustererkennung) Juan Vasquez Correa Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung) Elmar Nöth Professur für Informatik (Mustererkennung)

Involved external institutions

Ludwig-Maximilians-Universität (LMU) DE Germany (DE) Universidad de Antioquía (UDEA) CO Colombia (CO)

How to cite

APA:

Arias Vergara, T., Vasquez Correa, J., Gollwitzer, S., Orozco-Arroyave, J.R., Schuster, M., & Nöth, E. (2019). Multi-channel Convolutional Neural Networks for Automatic Detection of Speech Deficits in Cochlear Implant Users. In Ingela Nyström, Yanio Hernández Heredia, Vladimir Milián Núñez (Eds.), Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. (pp. 679-687).

MLA:

Arias Vergara, Tomás, et al. "Multi-channel Convolutional Neural Networks for Automatic Detection of Speech Deficits in Cochlear Implant Users." Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Ed. Ingela Nyström, Yanio Hernández Heredia, Vladimir Milián Núñez, 2019. 679-687.

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