A survey of speech emotion recognition in natural environment

MS Fahad, A Ranjan, J Yadav, A Deepak - Digital signal processing, 2021 - Elsevier
While speech emotion recognition (SER) has been an active research field since the last
three decades, the techniques that deal with the natural environment have only emerged in …

A survey on databases for multimodal emotion recognition and an introduction to the VIRI (visible and InfraRed image) database

MFH Siddiqui, P Dhakal, X Yang, AY Javaid - Multimodal Technologies …, 2022 - mdpi.com
Multimodal human–computer interaction (HCI) systems pledge a more human–human-like
interaction between machines and humans. Their prowess in emanating an unambiguous …

MSP-IMPROV: An acted corpus of dyadic interactions to study emotion perception

C Busso, S Parthasarathy, A Burmania… - IEEE Transactions …, 2016 - ieeexplore.ieee.org
We present the MSP-IMPROV corpus, a multimodal emotional database, where the goal is
to have control over lexical content and emotion while also promoting naturalness in the …

Speech emotion recognition using Fourier parameters

K Wang, N An, BN Li, Y Zhang… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
Recently, studies have been performed on harmony features for speech emotion
recognition. It is found in our study that the first-and second-order differences of harmony …

Speech emotion recognition using support vector machine

M Jain, S Narayan, P Balaji, A Bhowmick… - arXiv preprint arXiv …, 2020 - arxiv.org
In this project, we aim to classify the speech taken as one of the four emotions namely,
sadness, anger, fear and happiness. The samples that have been taken to complete this …

Curriculum learning for speech emotion recognition from crowdsourced labels

R Lotfian, C Busso - IEEE/ACM Transactions on Audio, Speech …, 2019 - ieeexplore.ieee.org
This study introduces a method to design a curriculum for machine-learning to maximize the
efficiency during the training process of deep neural networks (DNNs) for speech emotion …

Towards a small set of robust acoustic features for emotion recognition: challenges

M Tahon, L Devillers - … ACM transactions on audio, speech, and …, 2015 - ieeexplore.ieee.org
The search of a small acoustic feature set for emotion recognition faces three main
challenges. Such a feature set must be robust to large diversity of contexts in real-life …

Deep speaker conditioning for speech emotion recognition

A Triantafyllopoulos, S Liu… - 2021 IEEE international …, 2021 - ieeexplore.ieee.org
In this work, we explore the use of speaker conditioning sub-networks for speaker
adaptation in a deep neural network (DNN) based speech emotion recognition (SER) …

Personalised depression forecasting using mobile sensor data and ecological momentary assessment

A Kathan, M Harrer, L Küster… - Frontiers in digital …, 2022 - frontiersin.org
Introduction Digital health interventions are an effective way to treat depression, but it is still
largely unclear how patients' individual symptoms evolve dynamically during such …

A personalised approach to audiovisual humour recognition and its individual-level fairness

A Kathan, S Amiriparian, L Christ… - Proceedings of the 3rd …, 2022 - dl.acm.org
Humour is one of the most subtle and contextualised behavioural patterns to study in social
psychology and has a major impact on human emotions, social cognition, behaviour, and …