In this work, we study the use of attention mechanisms to enhance the performance of the
state-of-the-art deep learning model in Speech Emotion Recognition (SER). We introduce a …

In sequence modeling tasks the token order matters, but this information can be partially lost
due to the discretization of the sequence into data points. In this paper, we study the …

Operant motives are unconscious intrinsic desires that can be measured by implicit methods,
such as the Operant Motive Test (OMT) employs. During the OMT, participants are asked to …

Speech emotion recognition (SER) is always challenging because of factors such as emotional
corpus, acoustic features and SER modeling. SER based on deep learning are limited to …

Notwithstanding the significant advancements in the field of deep learning, the basic long
short-term memory (LSTM) or Gated Recurrent Unit (GRU) units have largely remained …

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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, …

… CONTEXT-AWARE ATTENTION MECHANISM FOR SPEECH EMOTION RECOGNITION,
Gaetan Ramet, Philip N. Garner, Michael Baeriswyl and Alexandros Lazaridis, in: IEEE …

After how many drinks does someone experience acute consequences-determining thresholds
for binge drinking based on two event-level studies: Optimal thresholds for binge drinking…

Improving the conditioning of the optimization criterion in acoustic multi-channel equalization
using shorter reshaping filters, Ina Kodrasi and Simon Doclo, in: EURASIP Journal on …