'Soundscapes' are an increasingly active topic in Human-Computer Interaction (HCI) and
interaction design. From mapping acoustic environments through sound recordings to …

Crowdsourcing is a popular tool for collecting large amounts of annotated data, but the
specific format of the strong labels necessary for sound event detection is not easily …

SONYC Urban Sound Tagging (SONYC-UST) is a dataset for the development and
evaluation of machine listening systems for real-world urban noise monitoring. It consists of …

Deep learning work on musical instrument recognition has generally focused on instrument
classes for which we have abundant data. In this work, we exploit hierarchical relationships …

In this paper, we study the use of soft labels to train a system for sound event detection
(SED). Soft labels can result from annotations which account for human uncertainty about …

Noise pollution is among the most consistently cited and highest impact quality-of-life issues
in major urban areas across the US, with more than 70 million people estimated to be …

Noise pollution is one of the topmost quality of life issues for urban residents in the United
States. Continued exposure to high levels of noise has proven effects on health, including …

We present SONYC-UST-V2, a dataset for urban sound tagging with spatiotemporal
information. This dataset is aimed for the development and evaluation of machine listening …

Crowdsourcing has become a common approach for annotating large amounts of data. It
has the advantage of harnessing a large workforce to produce large amounts of data in a …

While there has been much recent progress using deep learning techniques to separate
speech and music audio signals, these systems typically require large collections of isolated …