Data augmentation and deep learning methods in sound classification: A systematic review

OO Abayomi-Alli, R Damaševičius, A Qazi… - Electronics, 2022 - mdpi.com
The aim of this systematic literature review (SLR) is to identify and critically evaluate current
research advancements with respect to small data and the use of data augmentation …

Is speech the new blood? recent progress in ai-based disease detection from audio in a nutshell

M Milling, FB Pokorny, KD Bartl-Pokorny… - Frontiers in digital …, 2022 - frontiersin.org
In recent years, advancements in the field of artificial intelligence (AI) have impacted several
areas of research and application. Besides more prominent examples like self-driving cars …

openXBOW--Introducing the Passau open-source crossmodal Bag-of-Words toolkit

M Schmitt, B Schuller - Journal of Machine Learning Research, 2017 - jmlr.org
We introduce openXBOW, an open-source toolkit for the generation of bag-of-words (BoW)
representations from multimodal input. In the BoW principle, word histograms were first used …

The interspeech 2017 computational paralinguistics challenge: Addressee, cold & snoring

B Schuller, S Steidl, A Batliner, E Bergelson… - Computational …, 2017 - pure.mpg.de
Abstract The INTERSPEECH 2017 Computational Paralinguistics Challenge addresses
three different problems for the first time in research competition under well-defined …

The interspeech 2018 computational paralinguistics challenge: Atypical & self-assessed affect, crying & heart beats

BW Schuller, S Steidl, A Batliner… - … Annual Conference of …, 2018 - oulurepo.oulu.fi
Abstract The INTERSPEECH 2018 Computational Paralinguistics Challenge addresses four
different problems for the first time in a research competition under well-defined conditions …

[PDF][PDF] The interspeech 2019 computational paralinguistics challenge: Styrian dialects, continuous sleepiness, baby sounds & orca activity

B Schuller, A Batliner, C Bergler, FB Pokorny… - 2019 - opus.bibliothek.uni-augsburg.de
Abstract The INTERSPEECH 2019 Computational Paralinguistics Challenge addresses four
different problems for the first time in a research competition under well-defined conditions …

Can machine learning assist locating the excitation of snore sound? A review

K Qian, C Janott, M Schmitt, Z Zhang… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
In the past three decades, snoring (affecting more than 30% adults of the UK population) has
been increasingly studied in the transdisciplinary research community involving medicine …

Snoring classified: the Munich-Passau snore sound corpus

C Janott, M Schmitt, Y Zhang, K Qian, V Pandit… - Computers in Biology …, 2018 - Elsevier
Objective Snoring can be excited in different locations within the upper airways during sleep.
It was hypothesised that the excitation locations are correlated with distinct acoustic …

[HTML][HTML] Prediction of the obstruction sites in the upper airway in sleep-disordered breathing based on snoring sound parameters: a systematic review

Z Huang, G Aarab, MJL Ravesloot, N Zhou… - Sleep Medicine, 2021 - Elsevier
Background Identification of the obstruction site in the upper airway may help in treatment
selection for patients with sleep-disordered breathing. Because of limitations of existing …

A bag of wavelet features for snore sound classification

K Qian, M Schmitt, C Janott, Z Zhang, C Heiser… - Annals of Biomedical …, 2019 - Springer
Snore sound (SnS) classification can support a targeted surgical approach to sleep related
breathing disorders. Using machine listening methods, we aim to find the location of …