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 …
research advancements with respect to small data and the use of data augmentation …
Covid-19 and computer audition: An overview on what speech & sound analysis could contribute in the sars-cov-2 corona crisis
At the time of writing this article, the world population is suffering from more than 2 million
registered COVID-19 disease epidemic-induced deaths since the outbreak of the corona …
registered COVID-19 disease epidemic-induced deaths since the outbreak of the corona …
[PDF][PDF] Snore sound classification using image-based deep spectrum features
In this paper, we propose a method for automatically detecting various types of snore
sounds using image classification convolutional neural network (CNN) descriptors extracted …
sounds using image classification convolutional neural network (CNN) descriptors extracted …
Speech analysis for health: Current state-of-the-art and the increasing impact of deep learning
Due to the complex and intricate nature associated with their production, the acoustic-
prosodic properties of a speech signal are modulated with a range of health related effects …
prosodic properties of a speech signal are modulated with a range of health related effects …
What do North American babies hear? A large‐scale cross‐corpus analysis
A range of demographic variables influences how much speech young children hear.
However, because studies have used vastly different sampling methods, quantitative …
However, because studies have used vastly different sampling methods, quantitative …
End-to-end multimodal affect recognition in real-world environments
Automatic affect recognition in real-world environments is an important task towards a
natural interaction between humans and machines. The recent years, several …
natural interaction between humans and machines. The recent years, several …
Crafting adversarial examples for speech paralinguistics applications
Y Gong, C Poellabauer - arXiv preprint arXiv:1711.03280, 2017 - arxiv.org
Computational paralinguistic analysis is increasingly being used in a wide range of cyber
applications, including security-sensitive applications such as speaker verification …
applications, including security-sensitive applications such as speaker verification …
Sinusoidal model-based diagnosis of the common cold from the speech signal
Background and objective: Developing speech signal-based non-invasive diagnosis
techniques is an emerging research field in biomedical signal processing. Detecting the …
techniques is an emerging research field in biomedical signal processing. Detecting the …
Dilated residual network with multi-head self-attention for speech emotion recognition
Speech emotion recognition (SER) plays an important role in intelligent speech interaction.
One vital challenge in SER is to extract emotion-relevant features from speech signals. In …
One vital challenge in SER is to extract emotion-relevant features from speech signals. In …
Everyday language input and production in 1,001 children from six continents
E Bergelson, M Soderstrom… - Proceedings of the …, 2023 - National Acad Sciences
Language is a universal human ability, acquired readily by young children, who otherwise
struggle with many basics of survival. And yet, language ability is variable across …
struggle with many basics of survival. And yet, language ability is variable across …