Detecting Lombard Speech Using Deep Learning Approach.

Robust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect.

Real-Time Maritime Traffic Anomaly Detection Based on Sensors and History Data Embedding.

The automated identification system of vessel movements receives a huge amount of multivariate, heterogeneous sensor data, which should be analyzed to make a proper and timely decision on vessel movements. The large number of vessels makes it difficult and time-consuming to detect abnormalities, thus rapid response algorithms should be developed for a decision support system to identify abnormal movements of vessels in areas of heavy traffic. This paper extends the previous study on a self-organizing map application for processing of sensor stream data received by the maritime automated identification system.

Recurrent laryngeal nerve injury assessment by intraoperative laryngeal ultrasonography: a prospective diagnostic test accuracy study.

Introduction: Recurrent laryngeal nerve injury is one of the major complications related to thyroid surgery. Intraoperative recurrent laryngeal nerve functional status monitoring is becoming a standard part of thyroid surgery. However, the current methods for intraoperative nerve functional status assessment are associated with a demand for specialized devices and increased costs.