A significant amount of energy is wasted in industrial operations due to several factors such as electricity theft, fraud, billing errors, and fault devices, among others. It is important to monitor the behavior of the electricity consumption in order to improve energy usage efficiency. Smart meters have been developed in order to collect information about the electricity consumption behaviors and lifestyles of the consumers. One of the most important applications to monitor energy consumption corresponds to anomaly detection. The main challenge in this application is the lack of fully labeled datasets with annotated information about the presence of anomalies in the time-series. The prpject proposes an unsupervised approach where a deep learning strategy that combines autoencoders and recurrent neural networks is used to detect anomalies in time-series of energy consumption.
Asynchronous Non-Intrusive Multi-Modal Analysis of Bio-Signals for the Automatic evaluation of the Neurological State of People With Parkinson's Disease
There are a lot of features that can be extracted from speech signals for different applications such as automatic speech recognition or speaker verification. However, for pathological speech processing there is a need to extract features about the …
To solve the task of surgical mask detection from audio recordings in the scope of Interspeech’s ComParE challenge, we introduce a phonetic recognizer which is able to differentiate between clear and mask samples. A deep recurrent phoneme recognition …
Parkinson's disease is a neurodegenerative disorder characterized by a variety of motor and non-motor symptoms. Particularly, several speech impairments appear in the initial stages of the disease, which affect aspects related to respiration and the …
Parkinson's disease is a neurodegenerative disorder characterized by a variety of motor symptoms. Particularly, difficulties to start/stop movements have been observed in patients. From a technical/diagnostic point of view, these movement changes can …
Speech impairments are one of the earliest manifestations in patients with Parkinson’s disease. Particularly, articulation deficits related to the capability of the speaker to start/stop the vibration of the vocal folds have been observed in the …