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Analyzing GMMs to characterize resonance anomalies in speakers suffering from apnoea.

, , , , , and . INTERSPEECH, page 1459-1462. ISCA, (2009)

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Embodied conversational agents for voice-biometric interfaces., , , , and . ICMI, page 305-312. ACM, (2008)Driver Identification and Verification From Smartphone Accelerometers Using Deep Neural Networks., , and . IEEE Trans. Intell. Transp. Syst., 23 (1): 97-109 (2022)Data-Driven Performance Evaluation Framework for Multi-Modal Public Transport Systems., , , and . Sensors, 22 (1): 17 (2022)Analyzing GMMs to characterize resonance anomalies in speakers suffering from apnoea., , , , , and . INTERSPEECH, page 1459-1462. ISCA, (2009)Using HMM to Detect Speakers with Severe Obstructive Sleep Apnoea Syndrome., , , , , and . IberSPEECH, volume 328 of Communications in Computer and Information Science, page 121-128. Springer, (2012)Data-Driven Analysis of Bicycle Sharing Systems as Public Transport Systems Based on a Trip Index Classification., , , , , and . Sensors, 20 (15): 4315 (2020)Introducing Non-linear Analysis into Sustained Speech Characterization to Improve Sleep Apnea Detection., , , and . NOLISP, volume 7015 of Lecture Notes in Computer Science, page 215-223. Springer, (2011)Deep Neural Networks for Driver Identification Using Accelerometer Signals from Smartphones., , and . BIS (2), volume 354 of Lecture Notes in Business Information Processing, page 206-220. Springer, (2019)Speech Signal and Facial Image Processing for Obstructive Sleep Apnea Assessment., , , , , and . Comput. Math. Methods Medicine, (2015)Assessment of Severe Apnoea through Voice Analysis, Automatic Speech, and Speaker Recognition Techniques., , , , , and . EURASIP J. Adv. Signal Process., (2009)