Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge
More than a decade has passed since research on automatic recognition of emotion from
speech has become a new field of research in line with its 'big brothers' speech and speaker …
speech has become a new field of research in line with its 'big brothers' speech and speaker …
[HTML][HTML] An ongoing review of speech emotion recognition
User emotional status recognition is becoming a key feature in advanced Human Computer
Interfaces (HCI). A key source of emotional information is the spoken expression, which may …
Interfaces (HCI). A key source of emotional information is the spoken expression, which may …
Evaluating deep learning architectures for speech emotion recognition
Abstract Speech Emotion Recognition (SER) can be regarded as a static or dynamic
classification problem, which makes SER an excellent test bed for investigating and …
classification problem, which makes SER an excellent test bed for investigating and …
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 …
Prediction of asynchronous dimensional emotion ratings from audiovisual and physiological data
Automatic emotion recognition systems based on supervised machine learning require
reliable annotation of affective behaviours to build useful models. Whereas the dimensional …
reliable annotation of affective behaviours to build useful models. Whereas the dimensional …
Class-level spectral features for emotion recognition
The most common approaches to automatic emotion recognition rely on utterance-level
prosodic features. Recent studies have shown that utterance-level statistics of segmental …
prosodic features. Recent studies have shown that utterance-level statistics of segmental …
[HTML][HTML] In-depth investigation of speech emotion recognition studies from past to present The importance of emotion recognition from speech signal for AI
In the super smart society (Society 5.0), new and rapid methods are needed for speech
recognition, emotion recognition, and speech emotion recognition areas to maximize human …
recognition, emotion recognition, and speech emotion recognition areas to maximize human …
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 …
Feature analysis and evaluation for automatic emotion identification in speech
The definition of parameters is a crucial step in the development of a system for identifying
emotions in speech. Although there is no agreement on which are the best features for this …
emotions in speech. Although there is no agreement on which are the best features for this …
Speaker-sensitive emotion recognition via ranking: Studies on acted and spontaneous speech
We introduce a ranking approach for emotion recognition which naturally incorporates
information about the general expressivity of speakers. We demonstrate that our approach …
information about the general expressivity of speakers. We demonstrate that our approach …