This article is a survey of deep learning methods for single and multiple sound source
localization, with a focus on sound source localization in indoor environments, where …

Audio pattern recognition is an important research topic in the machine learning area, and
includes several tasks such as audio tagging, acoustic scene classification, music …

Sound event localization and detection is a novel area of research that emerged from the
combined interest of analyzing the acoustic scene in terms of the spatial and temporal …

This work defines a new framework for performance evaluation of polyphonic sound event
detection (SED) systems, which overcomes the limitations of the conventional collar-based …

Sound event detection (SED) is a task to detect sound events in an audio recording. One
challenge of the SED task is that many datasets such as the Detection and Classification of …

Automated audio captioning, a task that mimics human perception as well as innovatively
links audio processing and natural language processing, has overseen much progress over …

Symbolic music datasets are important for music information retrieval and musical analysis.
However, there is a lack of large-scale symbolic datasets for classical piano music. In this …

Eavesdropping on private conversations is one of the most common yet detrimental threats
to privacy. A number of recent works have explored side-channels on smart devices for …

Sound event detection (SED) and localization refer to recognizing sound events and
estimating their spatial and temporal locations. Using neural networks has become the …

Acoustic Scene Classification (ASC) is a task that classifies a scene according to
environmental acoustic signals. Audios collected from different cities and devices often …