We introduce TUT Acoustic Scenes 2016 database for environmental sound research,
consisting of binaural recordings from 15 different acoustic environments. A subset of this …

Automatic urban sound classification is a growing area of research with applications in
multimedia retrieval and urban informatics. In this paper we identify two main barriers to …

In this paper we present an approach to polyphonic sound event detection in real life
recordings based on bi-directional long short term memory (BLSTM) recurrent neural …

This paper presents and discusses various metrics proposed for evaluation of polyphonic
sound event detection systems used in realistic situations where there are typically multiple …

We propose a novel method for Acoustic Event Detection (AED). In contrast to speech,
sounds coming from acoustic events may be produced by a wide variety of sources …

Recent studies have demonstrated the potential of unsupervised feature learning for sound
classification. In this paper we further explore the application of the spherical k-means …

This paper presents a system for acoustic event detection in recordings from real life
environments. The events are modeled using a network of hidden Markov models; their size …

This paper proposes to use low-level spatial features extracted from multichannel audio for
sound event detection. We extend the convolutional recurrent neural network to handle …

We propose a new deep network for audio event recognition, called AENet. In contrast to
speech, sounds coming from audio events may be produced by a wide variety of sources …

Abstract The work presented in this article studies how the context information can be used
in the automatic sound event detection process, and how the detection system can benefit …