The MediaTeam Emotional Speech Corpus is currently the largest database of emotional speech for colloquial modern Finnish, containing simulated emotional content. The specific aim of the research is to investigate in detail the phonetic and phonological/linguistic correlates of basic or primary emotions in spoken Finnish, to develop statistical classification methods of emotional speech signals...

The automatic recognition of emotion from speech is a mature research field with a large number of publicly available corpora. However, to the best of the authors knowledge, none of these datasets consist solely of emotional speech samples from individuals with mental, neurological and/or physical disabilities. Yet, such individuals could benefit from speech-based assistive technologies to enha...

Several experiments have been carried out that revealed weaknesses of the current Text-To-Speech (TTS) systems in their emotional expressivity. Although some TTS systems allow XML-based representations of prosodic and/or phonetic variables, few publications considered, as a pre-processing stage, the use of intelligent text processing to detect affective information that can be used to tailor th...

Currently, an essential point in speech synthesis is the addressing of the variability of human speech. One of the main sources of this diversity is the emotional state of the speaker. Most of the recent work in this area has been focused on the prosodic aspects of speech and on rule-based formantsynthesis experiments. Even when adopting an improved voice source, we cannot achieve a smiling hap...

Emotional speech recognition has been studied using different approaches, which some works use real emotions and other uses acted ones, usually real emotional speech databases include like two or three emotions and acted ones have five or more, for this work Berlin Emotional Speech Database [1] was selected due to its availability, which has 535 sentences expressed in seven emotions (anger, bor...

In this paper, we propose the linear model of the relationship between the physical changes in speech and perceived emotional concepts. We make use of orthogonal bases in spite of emotional words and physical parameters themselves in order to avoid dependence on the method of selecting words and parameters. Furthermore we regard the emotions that listeners perceive from speech as the standard o...

This paper presents an approach to emotion recognition from speech signals. In this approach, the intonation groups (IGs) of the input speech signals are firstly extracted. The speech features in each selected intonation group are then extracted. With the assumption of linear mapping between feature spaces in different emotional states, a feature compensation approach is proposed to characteriz...

This paper describes an initial approach to emotional speech synthesis in Catalan based on a diphone concatenation TTS system. The main goal of this work is to develop a simple prosodic model for expressive synthesis. This model is obtained from an emotional speech collection artificially generated by means of a copy-prosody experiment. After validating the emotional content of this collection,...

This paper describes the collection and analysis of a multistyle emotional speech corpus, accomplished to study the variations of some acoustical parameters. Specifically, three emotional styles were considered: happiness, sadness and anger. Speech data in a neutral style were also collected, and prosodic differences of each style with respect to this neutral baseline were quantified. According...

The ability for humans to understand and process the emotional content of speech is unsurpassed by simulated intelligent agents. Beyond the linguistic content of speech are the underlying prosodic features naturally understood by humans. The goal of emotional speech processing systems is to extract and classify human speech for these so called paralinguistic elements. Presented here is a proof-...