It has been reported that vocal emotion recognition is challenging for cochlear implant (CI) listeners due to the limited spectral cues with CI devices. As the mechanism of CI, modulation information is provided as a primarily cue. Previous studies have revealed that the modulation components of speech are important for speech intelligibility. However, it is unclear whether modulation informati...

Spoken dialog systems (SDS) integrated into human-machine interaction interfaces is becoming a standard technology. Current state-of-the-art SDS, usually, is not able to provide for the user a natural way of communication. Existing automated dialog systems do not dedicate enough attention to problems in the interaction related to affected user behavior. As a result, Automatic Speech Recognition...

The report presents the process of planning, designing and the development of a database of spoken children’s speech whose native language is Bulgarian. The proposed model is designed for children between the age of 4 and 6 without speech disorders, and reflects their specific capabilities. At this age most children cannot read, there is no sustained concentration, they are emotional, etc. The ...

This introduction to a special session on “Emotion in recognition and synthesis” highlights the need to understand the effects of affective speaker states on voice and speech on a psychophysiological level. It is argued that major advances in speaker verification, speech recognition, and natural-sounding speech synthesis depend on increases in our knowledge of the mechanisms underlying voice an...

Recent work on emotional speech processing has demonstrated the interest to consider the information conveyed by the emotional component in speech to enhance the understanding of human behaviors. But to date, there has been little integration of emotion detection systems in effective applications. The present research focuses on the development of a fear-type emotions recognition system to dete...

This work is aimed at exploiting Second-Order Circular Suprasegmental Hidden Markov Models (CSPHMM2s) as classifiers to enhance talking condition recognition in stressful and emotional talking environments (completely two separate environments). The stressful talking environment that has been used in this work uses Speech Under Simulated and Actual Stress (SUSAS) database, while the emotional t...

Speech emotion recognition is one of the latest challenges in speech processing and Human Computer Interaction (HCI) in order to address the operational needs in real world applications. Besides human facial expressions, speech has proven to be one of the most promising modalities for automatic human emotion recognition. Speech is a spontaneous medium of perceiving emotions which provides in-de...

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...

Little is known about the underlying dimensions of impaired recognition of emotional prosody that is frequently observed in patients with Parkinson's disease (PD). Because patients with PD also suffer from working memory deficits and impaired time perception, the present study examined the contribution of (a) working memory (frontal executive functioning) and (b) processing of the acoustic para...