With the increase in the computing capabilities of the microprocessors it has now become possible to do real time computations on speech signals and images, so automatic emotion recognition through speech signals has become an important area of research. In this paper we have discussed the methods of extracting emotional features from a regular speech signals. Index Terms —Emotional feature; fe...

This paper describes some of the results of research into automatic recognition of children’s speech which has been conducted as part of the European Framework 5 ‘PF STAR’ project. Two new corpora of British English children’s speech are described. The first comprises over 14 hours of read data from 159 children, while the second includes 1 hour and 23 minutes of spontaneous and emotional speec...

Speech emotion recognition is currently an active research subject and has attracted extensive interest in the science community due to its vital application to human‐robot interaction. Most speech emotion recognition systems employ high‐dimensional speech features, indicating human emotion expression, to improve emotion recognition performance. To effectively reduce t...

This paper introduces a first approach to emotion recognition using RAMSES, the UPC’s speech recognition system. The approach is based on standard speech recognition technology using hidden semi-continuous Markov models. Both the selection of low level features and the design of the recognition system are addressed. Results are given on speaker dependent emotion recognition using the Spanish co...

Emotions are essential in developing interpersonal relationships. make emphasizing with others’ problems easy and leads to better communication without misunderstandings. Humans possess the natural ability of understanding emotions from their speech, hand gestures, facial expressions etc react accordingly but, it is impossible for machines extract understand unless they trained do so. Speech Em...

Speech Emotion Recognition (SER) is a hot research topic in the field of Human Computer Interaction (HCI). In this paper, we recognize three emotional states: happy, sad and neutral. The explored features include: energy, pitch, linear predictive spectrum coding (LPCC), Mel-frequency spectrum coefficients (MFCC), and Mel-energy spectrum dynamic coefficients (MEDC). A German Corpus (Berlin Datab...

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...

Machine-based emotional intelligence is a requirement for more natural interaction between humans and computer interfaces and a basic level of accurate emotion perception is needed for computer systems to respond adequately to human emotion. Humans convey emotional information both intentionally and unintentionally via speech patterns. These vocal patterns are perceived and understood by listen...

This paper presents our investigations on emotional state categorization from speech signals with a psychologically inspired computational model against human performance under the same experimental setup. Based on psychological studies, we propose a multistage categorization strategy which allows establishing an automatic categorization model flexibly for a given emotional speech categorizatio...

This paper describes the speech interface of a multimodal application developed as part of a study in intelligent multimedia. The application centres on a pet-like autonomous agent “Bouncy” and users communicate with the agent through speech, gestures, and eye contact. The interface concentrates on extra-linguistic properties of the speech signal, pitch and speech rate, involving no actual “spe...