Sound Event Detection
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Learning Sound Event Classifiers from Web Audio with Noisy Labels
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.
Adaptive pooling operators for weakly labeled sound event detection
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 TIME SERIES
A Closer Look at Weak Label Learning for Audio Events
• ankitshah009/WALNet-Weak_Label_Analysis
In this work, we first describe a CNN based approach for weakly supervised training of audio events.
Recurrent Neural Networks for Polyphonic Sound Event Detection in Real Life Recordings
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 networks (RNNs).
Robust sound event detection in bioacoustic sensor networks
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.
Language Modelling for Sound Event Detection with Teacher Forcing and Scheduled Sampling
• dr-costas/SEDLM
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On the contrary, with our method there is a decrease of 10% at F1 score and an increase of 11% at ER for the TUT-SED Synthetic 2016 dataset.
LANGUAGE MODELLING MACHINE TRANSLATION SOUND EVENT DETECTION
Convolutional Recurrent Neural Networks for Polyphonic Sound Event Detection
• cchinchristopherj/Right-Whale-Unsupervised-Model
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Sound events often occur in unstructured environments where they exhibit wide variations in their frequency content and temporal structure.