Emotion Recognition

Incorporating End-to-End Speech Recognition Models for Sentiment Analysis

Previous work on emotion recognition demonstrated a synergistic effect of combining several modalities such as auditory, visual, and transcribed text, to estimate the affective state of a speaker. Among these, the linguistic modality is crucial for …

On the Robustness of Speech Emotion Recognition for Human-Robot Interaction with Deep Neural Networks

Speech emotion recognition (SER) is an important aspect of effective human-robot collaboration and received a lot of attention from the research community. For example, many neural network-based architectures were proposed recently and pushed the …

EmoRL: Real-time Acoustic Emotion Classification using Deep Reinforcement Learning

Acoustically expressed emotions can make communication with a robot more efficient. Detecting emotions like anger could provide a clue for the robot indicating unsafe/undesired situations. Recently, several deep neural network-based models have been …