Emotional speech synthesis by XML file using interactive genetic algorithms

Lv, Siliang; Wang, Shangfei; Wang, Xufa

doi:10.1145/1543834.1543972

Cited by 4 publications

(2 citation statements)

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“…Their evaluation results show that a database with neutral semantic content should be used for emotional speech synthesis. Siliang et al introduce an emotional speech synthesis process, by adjusting the parameters (XML-tags) used to synthesise emotional speech dynamically, using interactive Genetic Algorithms [87]. For an overview on emotional speech synthesis and its practical applications see [88].…”

Section: A Speechmentioning

confidence: 99%

Emotion representation, analysis and synthesis in continuous space: A survey

Güneş

Schuller

Pantić

et al. 2011

Face and Gesture 2011

266

149

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Despite major advances within the affective computing research field, modelling, analysing, interpreting and responding to naturalistic human affective behaviour still remains as a challenge for automated systems as emotions are complex constructs with fuzzy boundaries and with substantial individual variations in expression and experience. Thus, a small number of discrete categories (e.g., happiness and sadness) may not reflect the subtlety and complexity of the affective states conveyed by such rich sources of information. Therefore, affective and behavioural computing researchers have recently invested increased effort in exploring how to best model, analyse, interpret and respond to the subtlety, complexity and continuity (represented along a continuum e.g., from-1 to +1) of affective behaviour in terms of latent dimensions (e.g., arousal, power and valence) and appraisals. Accordingly, this paper aims to present the current state of the art and the new challenges in automatic, dimensional and continuous analysis and synthesis of human emotional behaviour in an interdisciplinary perspective.

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Section: A Speechmentioning

confidence: 99%

Emotion representation, analysis and synthesis in continuous space: A survey

Güneş

Schuller

Pantić

et al. 2011

Face and Gesture 2011

266

149

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“…Whether the synthesized emotional speeches are understood by users and which emotion synthesizer is better are worthy of study. In this section, we assess two emotional speech synthesis algorithms, our algorithm [25], which uses an IGA to optimize prosody parameters, and the algorithm developed at MIT, the Affect Editor.…”

Section: Evaluation Experiments For Emotional Speech Synthesis Algorimentioning

confidence: 99%

Evaluating emotional algorithms using psychological scales

Wang

2009

Proceedings of the International Workshop on Affective-Aware Virtual Agents and Social Robots

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Evaluating the effectiveness of emotional algorithms is a challenge in the research of affective computing. This paper presents an evaluation method using psychological scales. Affective interfaces and artifacts generated by different emotional algorithms are regarded as the external stimuli, while users' feelings are regarded as subjective evaluations. Psychophysical methods, such as the Scheffe method of paired comparison, are adopted to measure users' feelings and obtain a psychological scale. Thus objects generated by different algorithms can be compared on this psychological scale. The higher the value, the better the algorithm is. Empirical studies on three kinds of emotional algorithms, namely emotional image retrieval, emotional speech synthesis, and emotional music generation, are used to illustrate various uses of our approach and how it may be applied to evaluating affective interaction and user-centered design.

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