Cross-corpus acoustic emotion recognition: Variances and strategies
As the recognition of emotion from speech has matured to a degree where it becomes
applicable in real-life settings, it is time for a realistic view on obtainable performances. Most …
applicable in real-life settings, it is time for a realistic view on obtainable performances. Most …
Combining long short-term memory and dynamic bayesian networks for incremental emotion-sensitive artificial listening
The automatic estimation of human affect from the speech signal is an important step
towards making virtual agents more natural and human-like. In this paper, we present a …
towards making virtual agents more natural and human-like. In this paper, we present a …
[PDF][PDF] Audio-visual feature selection and reduction for emotion classification.
S Haq, PJB Jackson, JD Edge - AVSP, 2008 - isca-archive.org
Recognition of expressed emotion from speech and facial gestures was investigated in
experiments on an audio-visual emotional database. A total of 106 audio and 240 visual …
experiments on an audio-visual emotional database. A total of 106 audio and 240 visual …
On-line emotion recognition in a 3-D activation-valence-time continuum using acoustic and linguistic cues
For many applications of emotion recognition, such as virtual agents, the system must select
responses while the user is speaking. This requires reliable on-line recognition of the user's …
responses while the user is speaking. This requires reliable on-line recognition of the user's …
Speech emotion recognition research: an analysis of research focus
This article analyses research in speech emotion recognition (“SER”) from 2006 to 2017 in
order to identify the current focus of research, and areas in which research is lacking. The …
order to identify the current focus of research, and areas in which research is lacking. The …
[PDF][PDF] Towards temporal modelling of categorical speech emotion recognition
W Han, H Ruan, X Chen, Z Wang, H Li, B Schuller - 2018 - opus.bibliothek.uni-augsburg.de
To model the categorical speech emotion recognition task in a temporal manner, the first
challenge arising is how to transfer the categorical label for each utterance into a label …
challenge arising is how to transfer the categorical label for each utterance into a label …
Pretext tasks selection for multitask self-supervised audio representation learning
Through solving pretext tasks, self-supervised learning leverages unlabeled data to extract
useful latent representations replacing traditional input features in the downstream task. In …
useful latent representations replacing traditional input features in the downstream task. In …
Iterative feature normalization scheme for automatic emotion detection from speech
The externalization of emotion is intrinsically speaker-dependent. A robust emotion
recognition system should be able to compensate for these differences across speakers. A …
recognition system should be able to compensate for these differences across speakers. A …
Recognizing affect from linguistic information in 3D continuous space
B Schuller - IEEE Transactions on Affective computing, 2011 - ieeexplore.ieee.org
Most research efforts dealing with recognition of emotion-related states from the human
speech signal concentrate on acoustic analysis. However, the last decade's research results …
speech signal concentrate on acoustic analysis. However, the last decade's research results …
A multitask approach to continuous five-dimensional affect sensing in natural speech
Automatic affect recognition is important for the ability of future technical systems to interact
with us socially in an intelligent way by understanding our current affective state. In recent …
with us socially in an intelligent way by understanding our current affective state. In recent …