PRS Summer 2020: Gammatone Convolutional Filters

Presentation on the Pattern Recognition Symposium 2020 Please ask your questions in the comments below! Corresponding Paper: Multi-channel Convolutional Neural Networks for Automatic Detection of Speech Deficits in Cochlear Implant Users Authors: Tomas Arias-Vergara, Juan Camilo Vasquez-Correa, Sandra Gollwitzer, Juan Rafael Orozco-Arroyave, Maria Schuster, Elmar Nöth Abstract: This paper proposes a methodology for the automatic detection of speech disorders in Cochlear Implant users by implementing a multi-channel Convolutional Neural Network. The model is fed with a 2-channel input which consists of two spectrograms computed from the speech signals using Mel-scaled and Gammatone filter banks. Speech recordings of 107 cochlear implant users (aged between 18 and 89 years old) and 94 healthy controls (aged between 20 and 64 years old) are considered for the tests. According to the results, using 2-channel spectrograms improves the performance of the classifier for automatic detection of speech impairments in Cochlear Implant users. References: https://link.springer.com/chapter/10.... https://iopscience.iop.org/chapter/97... Music Intro: Damiano Baldoni - Thinking of You https://freemusicarchive.org/music/Da... Music Outro: Damiano Baldoni - Poenia https://freemusicarchive.org/music/Da...