Speech analysis for health: Current state-of-the-art and the increasing impact of deep learning

N Cummins, A Baird, BW Schuller - Methods, 2018 - Elsevier
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 …

An overview of affective speech synthesis and conversion in the deep learning era

A Triantafyllopoulos, BW Schuller… - Proceedings of the …, 2023 - ieeexplore.ieee.org
Speech is the fundamental mode of human communication, and its synthesis has long been
a core priority in human–computer interaction research. In recent years, machines have …

The Geneva minimalistic acoustic parameter set (GeMAPS) for voice research and affective computing

F Eyben, KR Scherer, BW Schuller… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Work on voice sciences over recent decades has led to a proliferation of acoustic
parameters that are used quite selectively and are not always extracted in a similar fashion …

Deep learning for human affect recognition: Insights and new developments

PV Rouast, MTP Adam, R Chiong - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Automatic human affect recognition is a key step towards more natural human-computer
interaction. Recent trends include recognition in the wild using a fusion of audiovisual and …

Speech emotion recognition from 3D log-mel spectrograms with deep learning network

H Meng, T Yan, F Yuan, H Wei - IEEE access, 2019 - ieeexplore.ieee.org
Speech emotion recognition is a vital and challenging task that the feature extraction plays a
significant role in the SER performance. With the development of deep learning, we put our …

A survey of personality computing

A Vinciarelli, G Mohammadi - IEEE Transactions on Affective …, 2014 - ieeexplore.ieee.org
Personality is a psychological construct aimed at explaining the wide variety of human
behaviors in terms of a few, stable and measurable individual characteristics. In this respect …

Deep learning for robust feature generation in audiovisual emotion recognition

Y Kim, H Lee, EM Provost - 2013 IEEE international conference …, 2013 - ieeexplore.ieee.org
Automatic emotion recognition systems predict high-level affective content from low-level
human-centered signal cues. These systems have seen great improvements in classification …

Towards emotionally aware AI smart classroom: Current issues and directions for engineering and education

Y Kim, T Soyata, RF Behnagh - Ieee Access, 2018 - ieeexplore.ieee.org
Future smart classrooms that we envision will significantly enhance learning experience and
seamless communication among students and teachers using real-time sensing and …

Alzheimer's disease and automatic speech analysis: a review

MLB Pulido, JBA Hernández, MÁF Ballester… - Expert systems with …, 2020 - Elsevier
The objective of this paper is to present the state of-the-art relating to automatic speech and
voice analysis techniques as applied to the monitoring of patients suffering from Alzheimer's …

Multimodal fusion of bert-cnn and gated cnn representations for depression detection

M Rodrigues Makiuchi, T Warnita, K Uto… - Proceedings of the 9th …, 2019 - dl.acm.org
Depression is a common, but serious mental disorder that affects people all over the world.
Besides providing an easier way of diagnosing the disorder, a computer-aided automatic …