0449 Comparing Deep Feature Representations to Improve Robustness to Subject Variation in Snore Detection

• Published in: Sleep (New York, N.Y.) Vol. 42; no. Supplement_1; pp. A180 - A181
• Main Authors: Chaturvedi, Akhil, Goh, Chun Fan, Raina, Rahul Shailesh, Shimada, Kenji
• Format: Journal Article
• Language: English
• Published: Westchester Oxford University Press 13.04.2019
• Subjects: Accuracy

Introduction Snoring is an indicator of obstructive sleep apnea (OSA), which contributes to cardiovascular disease and mortality. To better study snoring, audio-based snore detection methods using different feature representations have been proposed. However, there is a gap in (1) baseline compariso...