We analyze two German databases: the OLLO database [1] designed for doing speech recognition experiments on speech variabilities, and the Berlin emotional database [2] designed for the analysis and synthesis of emotional speech. The paper tries to find a relation between intrinsic speech variabilities and the emotions. Moreover, we study this relation from the point of view of speech recognitio...

Recently recognition of emotions became very important in the field of speech and/or speaker recognition. This paper is dedicated to experimental investigation of best acoustic features obtained for purpose of gender-dependent speaker recognition from emotional speech. Four feature sets LPC (Linear Prediction Coefficients), LPCC (Linear Prediction Cepstral Coefficients), MFCC (Melfrequency Ceps...

Emotion recognition from speech has emerged as an important research area in the recent past. In this regard, review of existing work on emotional speech processing is useful for carrying out further research. In this paper, the recent literature on speech emotion recognition has been presented considering the issues related to emotional speech corpora, different types of speech features and mo...

Speech interaction with in-car systems is becoming more commonplace as systems improve. New cars are often equipped with speech recognition systems to dial phone numbers and or control the in-car environment, and with speech output to provide verbal directions from navigation systems. The paper explores the possibilities of richer speech interaction between driver and car with automatic recogni...

Emotion mismatch between training and testing will cause system performance decline sharply which is emotional speaker recognition. It is an important idea to solve this problem according to the emotion normalization of test speech. This method proceeds from analysis of the differences between every kind of emotional speech and neutral speech. Besides, it takes the baseband mismatch of emotiona...

Recognizing speakers in emotional conditions remains a challenging issue, since speaker states such as emotion affect the acoustic parameters used in typical speaker recognition systems. Thus, it is believed that knowledge of the current speaker emotion can improve speaker recognition in real life conditions. Conversely, speech emotion recognition still has to overcome several barriers before i...

In this paper we demonstrate how the emotional state of the speaker in uences his or her speech. We show that recognition accuracy varies signi cantly depending on the emotional state of the speaker. Our system models the pronunciation variation of emotional speech both at the acoustic and prosodic level. We show that using emotion-speci c acoustic and prosodic models allows the system to discr...

The presented paper is concerned with emotion recognition based on speech signal. Two novel elements introduced in the method are an introduction of novel set of emotional speech descriptors and an application of a binary-tree based classifier, where consecutive emotions are extracted at each node, based on an assessment of feature triplets. The method has been verified using two databases of e...