We present a comprehensive study on the effect of reverberation and background noise on the recognition of nonprototypical emotions from speech. We carry out our evaluation on a single, well-defined task based on the FAU Aibo Emotion Corpus consisting of spontaneous children’s speech, which was used in the INTERSPEECH 2009 Emotion Challenge, the first of its kind. Based on the challenge task, a...

Emotion plays an important role in human communications. We construct a framework for multi-modal fusion emotion recognition. Facial expression features and speech features are respectively extracted from image sequences and speech signals. In order to locate and track facial feature points, we construct an Active Appearance Model for facial images with all kinds of expressions. Facial Animatio...

Speech is a natural communication method used by humans. Speaker identification (SI) technology based on human speech has been as an entry point for many human-computer-interaction applications. The performance of SI models can degrade when dealing with expressive uttered in emotional situations because emotion databases do not have sufficient data to train various states. Generally, are traine...

In this paper, we address the issue of speaker-specific emotion detection (neutral vs emotion) from speech signals with models for neutral speech as reference. As emotional speech is produced by the human speech production mechanism, the emotion information is expected to lie in the features of both excitation source and the vocal tract system. Linear Prediction residual is used as the excitati...

In recent years a great deal of research has been done to automatically recognize emotions from human speech. Emotion is a symbol to express the feelings of one’s expression. It is also important to identify the emotion of the user to understand the feeling of an utterance. There are main three goals in speech emotion detection. First is to select appropriate features like energy, the pitch, LP...

In order to improve the recognition accuracy of speech emotion recognition, in this paper, a novel hierarchical method based on improved Decision Directed Acyclic Graph SVM (improved DDAGSVM) is proposed for speech emotion recognition. The improved DDAGSVM is constructed according to the confusion degrees of emotion pairs. In addition, a geodesic distance-based testing algorithm is proposed for...

In this paper, a Mandarin speech based emotion classification method is presented. Five primary human emotions including anger, boredom, happiness, neutral and sadness are investigated. In emotion classification of speech signals, conventional features are statistics of fundamental frequency, loudness, duration and voice quality. However, the recognition accuracy of systems employing these feat...

The present study investigates temporal characteristics of speech conveying emotion and attitude. First, a production study was conducted at the global level of the whole utterance, determining the p̋roduction values of “global speech rate” f̋or each emotion and attitude involved in the study. A perception study ̋ was also carried out at this global level, seeking perceptually optimal “global spe...

Feature extraction is still a disputed issue for the recognition of emotions from speech. Differences in features for male and female speakers are a well-known problem and it is established that gender-dependent emotion recognizers perform better than gender-independent ones. We propose a way to improve the discriminative quality of gender-dependent features: The emotion recognition system is p...

In this paper, we describe our approach of enabling an interactive dialogue system to recognize user emotion and sentiment in realtime. These modules allow otherwise conventional dialogue systems to have “empathy” and answer to the user while being aware of their emotion and intent. Emotion recognition from speech previously consists of feature engineering and machine learning where the first s...