language and emotion are two related systems in use, in that one system (emotions) impacts the performance of the other (language). both of them share their functionality in communication. since the nature of foreign language classrooms is ideally interactional, emotional intelligence (ei) gains importance. the aim of this study was to find out whether one's total emotional quotient and its com...

As research in speech processing has matured, attention has gradually shifted from linguistic-related applications such as speech recognition towards paralinguistic speech processing problems, in particular the recognition of speaker identity, language, emotion, gender, and age. Determination of a speaker’s emotion or mental state is a particularly challenging problem, in view of the significan...

Accurate emotion recognition from speech is important for applications like smart health care, smart entertainment, and other smart services. High accuracy emotion recognition from Chinese speech is challenging due to the complexities of the Chinese language. In this paper, we explore how to improve the accuracy of speech emotion recognition, including speech signal feature extraction and emoti...

This paper presents an approach to emotion recognition from speech signals and textual content. In the analysis of speech signals, thirty-three acoustic features are extracted from the speech input. After Principle Component Analysis (PCA) is performed, 14 principle components are selected for discriminative representation. In this representation, each principle component is the combination of ...

Few studies exist on the topic of emotion encoding in speech in the articulatory domain. In this report, we analyze articulatory data collected during simulated emotional speech production and investigate differences in speech articulation among four emotion types; neutral, anger, sadness and happiness. The movement data of the tongue tip, the jaw and the lower lip, along with speech, were obta...

Recent researches into human-machine communication make more emphasis on the recognition of nonverbal information, especially on the topic of emotional reaction. Many kinds of physiological characteristics are used to extract emotions, such as voice, facial expression, hand gesture, body movement, even heartbeat and blood pressure. In this paper, based on the idea that humans are capable of det...

A study of the automatic discrimination of emotion in three different time windows of speech is presented. A large corpus of acted emotional speech in Finnish was collected in five emotional states: neutral, sadness, joy, anger and tenderness. Automatic emotion discrimination tests were performed in speaker-independent scenarios using kNN classifiers with sequential forwards-backwards floating ...

In spontaneous speech, emotion information is embedded at several levels: acoustic, linguistic, gestural (non-verbal), etc. For emotion recognition in speech, there is much attention to acoustic level and some attention at the linguistic level. In this study, we identify paralinguistic markers for emotion in the language. We study two Indian languages belonging to two distinct language families...

We investigate the effect and usefulness of spontaneity in speech (i.e. whether a given speech data is spontaneous or not) in the context of emotion recognition. We hypothesize that emotional content in speech is interrelated with its spontaneity, and thus propose to use spontaneity classification as an auxiliary task to the problem of emotion recognition. We propose two supervised learning set...

Study of emotions in human-computer interaction is a growing research area. Focusing on automatic emotion recognition, work is being performed in order to achieve good results particularly in speech and facial gesture recognition. This paper presents a study where, using a wide range of speech parameters, improvement in emotion recognition rates is analyzed. Using an emotional multimodal biling...