In this study, we aim to learn highly descriptive representations for a wide set of machinery
sounds and exploit this knowledge to perform condition monitoring of mechanical …

The current paper introduces a multimodal framework to provide Web-TV automations for
live broadcasting and overall big streaming data management. The term indexing refers to …

Media authentication relies on the detection of inconsistencies that may indicate malicious
editing in audio and video files. Traditionally, authentication processes are performed by …

The current paper focuses on the development of an enhanced Mobile Journalism (MoJo)
model for soundscape heritage crowdsourcing, data-driven storytelling, and management in …

Modern feature-based methodologies in semantic audio applications attempt to capture the
temporal dependency of successive feature observations, which form the so-called texture …

Speech emotion recognition (SER) is crucial for enhancing affective computing and
enriching the domain of human-computer interaction. However, the main challenge in SER …

In the present work, a crowdsourcing approach is designed, to investigate the correlation
between air and noise pollution in urban areas. Citizens are requested to provide air quality …

Perceptually motivated audio signal processing and feature extraction have played a key
role in the determination of high-level semantic processes and the development of emerging …

This manuscript discusses the robustness to noise of deep learning models for two audio
classification tasks. The first task is a speaker recognition application, trying to identify five …

Deep learning has been applied to diverse audio semantics tasks, enabling the construction
of models that learn hierarchical levels of features from high-dimensional raw data …