In this paper, we consider both speaker dependent and listener dependent aspects in the assessment of emotions in speech. We model the speaker dependencies in emotional speech production by two parameters which describe the individual’s emotional expression behavior. Similarly, we model the listener’s emotion perception behavior by a simple parametric model. These models form a basis for improv...

Robots that can recognize emotions can improve humans’ mental health by providing empathy and social communication. Emotion recognition by robots is challenging because unlike in human-computer environments, facial information is not always available. Instead, our method proposes using speech and gait analysis to recognize human emotion. Previous research suggests that the dynamics of emotional...

Dyadic interactions encapsulate rich emotional exchange between interlocutors suggesting a multimodal, cross-speaker and cross-dimensional continuous emotion dependency. This study explores the dynamic inter-attribute emotional dependency at the cross-subject level with implications to continuous emotion recognition based on speech and body motion cues. We propose a novel two-stage Gaussian Mix...

In this paper, we proposed a weighted discrete K-nearest neighbor (weighted D-KNN) classification algorithm for detecting and evaluating emotion from Mandarin speech. In the experiments of the emotion recognition, Mandarin emotional speech database used contains five basic emotions, including anger, happiness, sadness, boredom and neutral, and the extracted acoustic features are Mel-Frequency C...

Emotion plays a significant role in cognitive psychology, behavioural sciences and humanoid robot design. The continuing improvements in speech recognition technology have led to many new and fascinating applications in human-computer interaction, context aware computing and computer mediated communication. A growing number of research studies in emotion recognition via an isolated short senten...

Researches in speech synthesis and speech analysis are underpinned by the databases they used. The performance of an emotion classifier relies heavily on the qualities of the training and testing data. A good database can make researches in these fields achieving better results. Hearing-impaired people are poor in presenting their emotions in speech. We want develop a computer-assisted speech t...

The authors have proposed a method of generating synthetic speech with emotion by creating three copora of emotional speech for use with CHATR [1][2], the concatenative speech synthesis system developed at ATR [3][4]. The corpora express joy, anger and sadness. For the previous trial, speech corpora were made with female voice. Having added speech corpora of male voice, the authors developed a ...

-Speech emotion recognition is a rapidly growing field of research that aims to automatically identify emotions from speech signals. This paper presents using machine learning techniques. The study begins by providing an overview the various approaches used in recognition, including feature extraction, selection, and classification. These selected features like pitch, MFCC are compared with exi...