Abstract: Speech emotion recognition (SER) is a crucial technology for applications such as human-computer interaction, mental health monitoring, and call centre analytics. However, SER research in ...

Abstract: Speech emotion recognition (SER) involves identifying a speaker’s emotional state from their speech utterance. Prior research has explored various cepstral features for developing SER ...

Background: Mental disorders have a significant impact on many areas of people’s life, particularly on affective regulation; thus, there is a growing need to find disease-specific biomarkers to ...

Speech emotion recognition base on Long Short-Term Model (LSTM), implemented in tensorflow. The system improve the accuracy of emotion recognition while maintaining lightweight through feature ...

QUANTICO, Va. (AP) — President Donald Trump on Tuesday proposed using American cities as training grounds for the armed forces and spoke of needing U.S. military might to combat what he called the ...

NEW YORK CITY — President Donald Trump used his address to the United Nations General Assembly to press for the release of hostages held by Hamas and condemn the flurry of US allies that recognized ...

In the wake of Charlie Kirk’s killing, President Trump and his allies have laid out a broad plan to target liberal groups, monitor speech, revoke visas and designate certain groups as domestic ...

In clinical settings, accurately understanding patients' emotions and responding appropriately plays a critical role in improving treatment outcomes and patient satisfaction. This technology acquires ...

In this tutorial, we walk through an advanced yet practical workflow using SpeechBrain. We start by generating our own clean speech samples with gTTS, deliberately adding noise to simulate real-world ...

ABSTRACT: This paper studies recent assistive technologies and AI sound detection systems that have been developed to support both the safety and communication of individuals who are deaf. It ...

Introduction: Emotion recognition based on electroencephalogram (EEG) signals has shown increasing application potential in fields such as brain-computer interfaces and affective computing. However, ...