Sound Event Detection

26 papers with code • 3 benchmarks • 13 datasets

Sound Event Detection (SED) is the task of recognizing the sound events and their respective temporal start and end time in a recording. Sound events in real life do not always occur in isolation, but tend to considerably overlap with each other. Recognizing such overlapping sound events is referred as polyphonic SED.

Source: A report on sound event detection with different binaural features

Greatest papers with code

Towards Deep Learning Models Resistant to Adversarial Attacks

tensorflow/cleverhans ICLR 2018

Its principled nature also enables us to identify methods for both training and attacking neural networks that are reliable and, in a certain sense, universal.

Adversarial Attack Adversarial Defense +2

Learning Sound Event Classifiers from Web Audio with Noisy Labels

lRomul/argus-freesound 4 Jan 2019

To foster the investigation of label noise in sound event classification we present FSDnoisy18k, a dataset containing 42. 5 hours of audio across 20 sound classes, including a small amount of manually-labeled data and a larger quantity of real-world noisy data.

General Classification Sound Event Detection

Ubicoustics: Plug-and-Play Acoustic Activity Recognition

FIGLAB/ubicoustics 14 Oct 2018

Despite sound being a rich source of information, computing devices with microphones do not leverage audio to glean useful insights about their physical and social context.

Activity Recognition Data Augmentation +2

Adaptive pooling operators for weakly labeled sound event detection

marl/autopool 26 Apr 2018

In this work, we treat SED as a multiple instance learning (MIL) problem, where training labels are static over a short excerpt, indicating the presence or absence of sound sources but not their temporal locality.

Multiple Instance Learning Sound Event Detection +1

Robust sound event detection in bioacoustic sensor networks

BirdVox/birdvoxdetect 20 May 2019

As a case study, we consider the problem of detecting avian flight calls from a ten-hour recording of nocturnal bird migration, recorded by a network of six ARUs in the presence of heterogeneous background noise.

Data Augmentation Sound Event Detection

Sound event detection in domestic environments withweakly labeled data and soundscape synthesis

turpaultn/DCASE2019_task4 26 Oct 2019

This paper presents Task 4 of the Detection and Classification of Acoustic Scenes and Events (DCASE) 2019 challenge and provides a first analysis of the challenge results.

Sound Event Detection

A Closer Look at Weak Label Learning for Audio Events

ankitshah009/WALNet-Weak_Label_Analysis 24 Apr 2018

In this work, we first describe a CNN based approach for weakly supervised training of audio events.

Audio Classification Sound Event Detection

Sound Event Detection with Depthwise Separable and Dilated Convolutions

dr-costas/dnd-sed 2 Feb 2020

The number of the channels of the CNNs and size of the weight matrices of the RNNs have a direct effect on the total amount of parameters of the SED method, which is to a couple of millions.

Sound Event Detection

SELD-TCN: Sound Event Localization & Detection via Temporal Convolutional Networks

JiuSenso/SELD-TCN 3 Mar 2020

The understanding of the surrounding environment plays a critical role in autonomous robotic systems, such as self-driving cars.

Acoustic Scene Classification Self-Driving Cars +1

DCASENET: A joint pre-trained deep neural network for detecting and classifying acoustic scenes and events

Jungjee/DcaseNet 21 Sep 2020

Single task deep neural networks that perform a target task among diverse cross-related tasks in the acoustic scene and event literature are being developed.

Acoustic Scene Classification Audio Tagging +1 Audio and Speech Processing