Sound plays a key role in human life and therefore sound recognition system has a great
future ahead. Sound classification and identification system has many applications such as …

To alleviate the problem of performance degradation due to the varied sound durations of
competing classes in sound event detection, we propose a method that utilizes multi-scale …

This paper presents a methodology for early detection of audio events from audio streams.
Early detection is the ability to infer an ongoing event during its initial stage. The proposed …

In this technique report, we present a polyphonic sound event detection (SED) system based
on a convolutional recurrent neural network for the task 4 of Detection and Classification of …

In this paper, we propose a system for rare sound event detection using a hierarchical and
multi-scaled approach based on Convolutional Neural Networks (CNN). The task consists …

The temporal and spectral structure is possessed in the time-frequency domain by sound
events. Analyzing and classifying acoustic environment using sound recording is an …

State-of-the-art sound event detection (SED) methods usually employ a series of
convolutional neural networks (CNNs) to extract useful features from the input audio signal …

This paper describes the model and training framework from our submission for DCASE
2017 task 3: sound event detection in real life audio. Extending the basic convolutional …

In sound event detection (SED), the representation ability of deep neural network (DNN)
models must be increased to significantly improve the accuracy or increase the number of …

Sound event detection systems typically consist of two stages: extracting hand-crafted
features from the raw audio waveform, and learning a mapping between these features and …