research
∙
07/20/2023
Comparison between transformers and convolutional models for fine-grained classification of insects
Fine-grained classification is challenging due to the difficulty of find...
share
research
∙
06/15/2023
Few-shot bioacoustic event detection at the DCASE 2023 challenge
Few-shot bioacoustic event detection consists in detecting sound events ...
research
∙
05/22/2023
Learning to detect an animal sound from five examples
Automatic detection and classification of animal sounds has many applica...
research
∙
10/14/2022
Full-Stack Bioacoustics: Field Kit to AI to Action (Workshop report)
Acoustic data (sound recordings) are a vital source of evidence for dete...
research
∙
07/13/2022
Polyphonic sound event detection for highly dense birdsong scenes
One hour before sunrise, one can experience the dawn chorus where birds ...
research
∙
12/13/2021
Computational bioacoustics with deep learning: a review and roadmap
Animal vocalisations and natural soundscapes are fascinating objects of ...
research
∙
10/11/2021
Rank-based loss for learning hierarchical representations
Hierarchical taxonomies are common in many contexts, and they are a very...
research
∙
12/06/2020
Guitar Effects Recognition and Parameter Estimation with Convolutional Neural Networks
Despite the popularity of guitar effects, there is very little existing ...
research
∙
10/05/2020
Short-term prediction of photovoltaic power generation using Gaussian process regression
Photovoltaic (PV) power is affected by weather conditions, making the po...
research
∙
08/13/2019
Estimating Mitigating the Impact of Acoustic Environments on Machine-to-Machine Signalling
The advance of technology for transmitting Data-over-Sound in various Io...
research
∙
05/08/2019
Efficient On-line Computation of Visibility Graphs
A visibility algorithm maps time series into complex networks following ...
research
∙
03/05/2019
Visibility graphs for robust harmonic similarity measures between audio spectra
Graph theory is emerging as a new source of tools for time series analys...
research
∙
01/31/2019
End-to-End Probabilistic Inference for Nonstationary Audio Analysis
A typical audio signal processing pipeline includes multiple disjoint an...
research
∙
11/06/2018
Unifying Probabilistic Models for Time-Frequency Analysis
In audio signal processing, probabilistic time-frequency models have man...
research
∙
11/06/2018
NIPS4Bplus: a richly annotated birdsong audio dataset
Recent advances in birdsong detection and classification have approached...
research
∙
10/30/2018
Sparse Gaussian process Audio Source Separation Using Spectrum Priors in the Time-Domain
Gaussian process (GP) audio source separation is a time-domain approach ...
research
∙
10/22/2018
Automatic acoustic identification of individual animals: Improving generalisation across species and recording conditions
Many animals emit vocal sounds which, independently from the sounds' fun...
research
∙
07/17/2018
Data-Efficient Weakly Supervised Learning for Low-Resource Audio Event Detection Using Deep Learning
We propose a method to perform audio event detection under the common co...
research
∙
07/16/2018
Automatic acoustic detection of birds through deep learning: the first Bird Audio Detection challenge
Assessing the presence and abundance of birds is important for monitorin...
research
∙
07/10/2018
Deep Learning for Audio Transcription on Low-Resource Datasets
In training a deep learning system to perform audio transcription, two p...
research
∙
07/10/2018
Deep Learning on Low-Resource Datasets
In training a deep learning system to perform audio transcription, two p...
research
∙
04/06/2018
Does k Matter? k-NN Hubness Analysis for Kernel Additive Modelling Vocal Separation
Kernel Additive Modelling (KAM) is a framework for source separation aim...
research
∙
02/02/2018
A Generative Model for Natural Sounds Based on Latent Force Modelling
Recent advances in analysis of subband amplitude envelopes of natural so...
research
∙
05/19/2017
Efficient Learning of Harmonic Priors for Pitch Detection in Polyphonic Music
Automatic music transcription (AMT) aims to infer a latent symbolic repr...
research
∙
06/03/2016
Gaussian Processes for Music Audio Modelling and Content Analysis
Real music signals are highly variable, yet they have strong statistical...
research
∙
09/20/2015
Denoising without access to clean data using a partitioned autoencoder
Training a denoising autoencoder neural network requires access to truly...
research
∙
11/13/2012
