Speech emotion recognition (SER) systems often struggle in real-world environments,
where ambient noise severely degrades their performance. This paper explores a novel …

In today's world, the interpretation of emotions from human speech has prompted a lot of
research attention in signal processing applications. Many speech recognition approaches …

A speech emotion recognition (SER) model for noisy environments is proposed, by using
four band-pass filtered speech waveforms as the model input instead of the simplified input …

Speech emotion recognition (SER) system can exploit an Speech enhancement (SE) model
to increase its noise robustness by suppressing the background noise. However, SE could …

The purpose of emotion recognition in conversation (ERC) is to identify the emotion category
of an utterance based on contextual information. Previous ERC methods relied on simple …

Speech emotion recognition (SER) is an indispensable component of any human machine
interactions, and enables building empathetic voice user interfaces. Ability to accurately …

A breakthrough in deep learning has led to improvements in speech emotion recognition
(SER), but these studies tend to process fixed-length segments, resulting in degraded …

In the natural environment, the received speech signal is often interfered by noise, which
reduces the performance of speech emotion recognition (SER) system. To this end, a noisy …

Emotion Sense for live call is a technology that is designed to detect emotions of the user
like happiness, sadness, anger, fear, etc. It is a Speech Emotion Recognition (SER) model …

Speech-based emotion recognition in machine learning is an emerging topic. In our daily
routine, whatever speech we communicate can be based on our mood or emotion that we …