Dawn of the transformer era in speech emotion recognition: closing the valence gap
J Wagner, A Triantafyllopoulos… - … on Pattern Analysis …, 2023 - ieeexplore.ieee.org
Recent advances in transformer-based architectures have shown promise in several
machine learning tasks. In the audio domain, such architectures have been successfully …
machine learning tasks. In the audio domain, such architectures have been successfully …
Probing speech emotion recognition transformers for linguistic knowledge
Large, pre-trained neural networks consisting of self-attention layers (transformers) have
recently achieved state-of-the-art results on several speech emotion recognition (SER) …
recently achieved state-of-the-art results on several speech emotion recognition (SER) …
Deep learning approaches for bimodal speech emotion recognition: Advancements, challenges, and a multi-learning model
Though acoustic speech emotion recognition has been studied for a while, bimodal speech
emotion recognition using both acoustic and text has gained momentum since speech …
emotion recognition using both acoustic and text has gained momentum since speech …
[HTML][HTML] Addressing data scarcity in speech emotion recognition: A comprehensive review
Speech emotion recognition (SER) is a critical field within affective computing, aiming to
detect and classify emotional states from speech signals, which vary dynamically over time …
detect and classify emotional states from speech signals, which vary dynamically over time …
Zero-shot personalization of speech foundation models for depressed mood monitoring
The monitoring of depressed mood plays an important role as a diagnostic tool in
psychotherapy. An automated analysis of speech can provide a non-invasive measurement …
psychotherapy. An automated analysis of speech can provide a non-invasive measurement …
The MERSA Dataset and a Transformer-Based Approach for Speech Emotion Recognition
E Zhang, R Trujillo, C Poellabauer - … of the 62nd Annual Meeting of …, 2024 - aclanthology.org
Research in the field of speech emotion recognition (SER) relies on the availability of
comprehensive datasets to make it possible to design accurate emotion detection models …
comprehensive datasets to make it possible to design accurate emotion detection models …
Fatigue prediction in outdoor running conditions using audio data
Although running is a common leisure activity and a core training regiment for several
athletes, between 29% and 79% of runners sustain an overuse injury each year. These …
athletes, between 29% and 79% of runners sustain an overuse injury each year. These …
A Residual Multi-Scale Convolutional Neural Network with Transformers for Speech Emotion Recognition
T Yan, H Meng, E Parada-Cabaleiro… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
The great variety of human emotional expression as well as the differences in the ways they
perceive and annotate them make Speech Emotion Recognition (SER) an ambiguous and …
perceive and annotate them make Speech Emotion Recognition (SER) an ambiguous and …
A residual multi-scale convolutional transformer network with chunk-level log-mel spectrograms for speech emotion recognition
T Yan, H Meng, E Parada-Cabaleiro, J Tao… - Authorea …, 2023 - techrxiv.org
The great variety of human emotional expression as well as the differences in the ways they
perceive and annotate them make Speech Emotion Recognition (SER) an ambiguous and …
perceive and annotate them make Speech Emotion Recognition (SER) an ambiguous and …
Audio Enhancement for Computer Audition—An Iterative Training Paradigm Using Sample Importance
Neural network models for audio tasks, such as automatic speech recognition (ASR) and
acoustic scene classification (ASC), are susceptible to noise contamination for real-life …
acoustic scene classification (ASC), are susceptible to noise contamination for real-life …