While speech emotion recognition (SER) has been an active research field since the last
three decades, the techniques that deal with the natural environment have only emerged in …

Research on speech processing has traditionally considered the task of designing hand-
engineered acoustic features (feature engineering) as a separate distinct problem from the …

Traditionally, speech emotion recognition (SER) research has relied on manually
handcrafted acoustic features using feature engineering. However, the design of …

Face recognition is of great importance to real world applications such as video surveillance,
human machine interaction and security systems. As compared to traditional machine …

Dimensional models have been proposed in psychology studies to represent complex
human emotional expressions. Activation and valence are two common dimensions in such …

In this paper, we show that convolutional neural networks can be directly applied to temporal
low-level acoustic features to identify emotionally salient regions without the need for …

The paper presents a Multi-Head Attention deep learning network for Speech Emotion
Recognition (SER) using Log mel-Filter Bank Energies (LFBE) spectral features as the input …

Many works have focused on speech emotion recognition algorithms. However, most rely on
the proper selection of speech acoustic features. In this paper, we propose a novel emotion …

This paper presents an approach based on acoustic analysis to describe gender equality in
French audiovisual streams, through the estimation of male and female speaking time …

Emotion recognition has been an active research area with both wide applications and big
challenges. This paper presents our effort for the Audio/Visual Emotion Challenge …