A survey of textual emotion recognition and its challenges
Textual language is the most natural carrier of human emotion. In natural language
processing, textual emotion recognition (TER) has become an important topic due to its …
processing, textual emotion recognition (TER) has become an important topic due to its …
A review of multimodal emotion recognition from datasets, preprocessing, features, and fusion methods
B Pan, K Hirota, Z Jia, Y Dai - Neurocomputing, 2023 - Elsevier
Affective computing is one of the most important research fields in modern human–computer
interaction (HCI). The goal of affective computing is to study and develop the theories …
interaction (HCI). The goal of affective computing is to study and develop the theories …
Survey of deep representation learning for speech emotion recognition
Traditionally, speech emotion recognition (SER) research has relied on manually
handcrafted acoustic features using feature engineering. However, the design of …
handcrafted acoustic features using feature engineering. However, the design of …
Domain invariant feature learning for speaker-independent speech emotion recognition
In this paper, we propose a novel domain invariant feature learning (DIFL) method to deal
with speaker-independent speech emotion recognition (SER). The basic idea of DIFL is to …
with speaker-independent speech emotion recognition (SER). The basic idea of DIFL is to …
Self supervised adversarial domain adaptation for cross-corpus and cross-language speech emotion recognition
Despite the recent advancement in speech emotion recognition (SER) within a single corpus
setting, the performance of these SER systems degrades significantly for cross-corpus and …
setting, the performance of these SER systems degrades significantly for cross-corpus and …
Speech emotion recognition based on formant characteristics feature extraction and phoneme type convergence
Abstract Speech Emotion Recognition (SER) has numerous applications including human-
robot interaction, online gaming, and health care assistance. While deep learning-based …
robot interaction, online gaming, and health care assistance. While deep learning-based …
CyTex: Transforming speech to textured images for speech emotion recognition
Speech emotion recognition is an important aspect of emotional state recognition in human–
machine interaction. Approaches using speech-to-image transforms have become popular …
machine interaction. Approaches using speech-to-image transforms have become popular …
Multimodal emotion recognition using transfer learning from speaker recognition and bert-based models
Automatic emotion recognition plays a key role in computer-human interaction as it has the
potential to enrich the next-generation artificial intelligence with emotional intelligence. It …
potential to enrich the next-generation artificial intelligence with emotional intelligence. It …
Multitask Transformer for Cross-Corpus Speech Emotion Recognition
Deep learning has significantly advanced the field of Speech Emotion Recognition (SER),
yet its efficacy in cross-corpus scenarios remains a challenge. To overcome this limitation …
yet its efficacy in cross-corpus scenarios remains a challenge. To overcome this limitation …
Improved speech emotion recognition using transfer learning and spectrogram augmentation
Automatic speech emotion recognition (SER) is a challenging task that plays a crucial role in
natural human-computer interaction. One of the main challenges in SER is data scarcity, ie …
natural human-computer interaction. One of the main challenges in SER is data scarcity, ie …