SPE-32.1
USING ACOUSTIC DEEP NEURAL NETWORK EMBEDDINGS TO DETECT MULTIPLE SCLEROSIS FROM SPEECH
Gábor Gosztolya, ELKH-SZTE Research Group on Artificial Intelligence, Hungary; László Tóth, University of Szeged, Hungary; Veronika Svindt, Ildikó Hoffmann, Research Center for Linguistics, Hungary; Judit Bóna, Eötvös Loránd University, Hungary
Session:
Language Disorders: Detection II
Track:
Speech and Language Processing
Location:
Gather Area E
Presentation Time:
Mon, 9 May, 23:00 - 23:45 China Time (UTC +8)
Mon, 9 May, 15:00 - 15:45 UTC
Mon, 9 May, 15:00 - 15:45 UTC
Session Chair:
Erfan Loweimi, King's College London
Session SPE-32
SPE-32.1: USING ACOUSTIC DEEP NEURAL NETWORK EMBEDDINGS TO DETECT MULTIPLE SCLEROSIS FROM SPEECH
Gábor Gosztolya, ELKH-SZTE Research Group on Artificial Intelligence, Hungary; László Tóth, University of Szeged, Hungary; Veronika Svindt, Ildikó Hoffmann, Research Center for Linguistics, Hungary; Judit Bóna, Eötvös Loránd University, Hungary
SPE-32.2: REPETITION ASSESSMENT FOR SPEECH AND LANGUAGE DISORDERS: A STUDY OF THE LOGOPENIC VARIANT OF PRIMARY PROGRESSIVE APHASIA
R'mani Haulcy, James Glass, Massachusetts Institute of Technology, United States of America; Katerina Placek, Brian Tracey, Takeda Pharmaceutical Company, United States of America; Adam Vogel, University of Melbourne/Redenlab Inc, Australia
SPE-32.3: SPEECH TASKS RELEVANT TO SLEEPINESS DETERMINED WITH DEEP TRANSFER LEARNING
Bang Tran, Youxiang Zhu, Xiaohui Liang, University of Massachusetts Boston, United States of America; James Schwoebel, Lindsay Warrenburg, Sonde Health Inc., United States of America