Modern Speech synthesisers have achieved a high degree of intelligibility, but can not be regarded as natural-sounding devices. In order to decrease the monotony of synthetic speech, the implementation of emotional effects is now being progressively considered. This paper presents a through study of emotional speech in Spanish, and its application to TTS, presenting a prototype system that simu...

Emotion is an important element in expressive speech synthesis. The paper makes the brief analysis on prosody parameters, stresses, rhythms and paralinguistic information in different emotional speech, and labels the speech with rich annotation information in multi-layers. Then, a CART model is used to do the emotional prosody generation. Unlike the traditional linear modification method, which...

Voice conversion method is applied to synthesizing emotional speech from standard reading (neutral) speech. Pairs of neutral speech and emotional speech are used for conversion rule training. The conversion adopts GMM (Gaussian Mixture Model) with DFW (Dynamic Frequency Warping). We also adopt STRAIGHT, the high-quality speech analysis-synthesis algorithm. As conversion target emotions, (Hot) a...

Emotional speech comprises of complex multimodal verbal and non-verbal information that allows deducting others' emotional states or thoughts in social interactions. While the neural correlates of verbal and non-verbal aspects and their interaction in emotional speech have been identified, there is very little evidence on how we perceive and resolve incongruity in emotional speech, and whether ...

Speech signal in addition to the linguistic information contains additional information about the speaker: age, gender, social status, accent (foreign accent, dialects, etc.), emotional state, health etc. Some of these informational channels induce changes of the speech acoustic characteristics. This article presents evaluation of the ASR acoustic models (first trained on neutral, read speech) ...

Speech signal in addition to the linguistic information contains additional information about the speaker: age, gender, social status, accent (foreign accent, dialects, etc.), emotional state, health etc. Some of these informational channels induce changes of the speech acoustic characteristics. This article presents evaluation of the ASR acoustic models (first trained on neutral, read speech) ...

The focus of this master’s thesis by the first author was to investigate the acoustic attributes of frustration in spontaneous speech. The speech material was recorded from real life Swedish telephone services by the company Voice Provider. The utterances were selected speaker by speaker in order to have at least one of them judged as emotionally neutral by a listener group, while the other utt...

D-scripts model is originally developed for description of affective (emotional) mass media texts and with extension also applies to emotional speech synthesis. In this model we distinguish units for “rational” inference (r-scripts) and units for “emotional” processing of meaning (d-scripts). Basing on a psycholinguistics study we demonstrate relations between classes of emotional utterances in...

The development of virtual story-telling is an ever ongoing process. As long as it does not perform on the same level as a human storyteller, there is room for improvement. The Virtual Storyteller, a project of the HMI department of the University of Twente, uses a Text-to-Speech application that creates synthetic speech from text input. It is definitely not a trivial matter to make synthetic s...

The present paper deals with the design and the annotation of a Greek real-world emotional speech corpus. The speech data consist of recordings collected during the interaction of naïve users with a smart-home dialogue system. Annotation of the speech data with respect to the uttered command and emotional state was performed. Initial experimentations towards recognizing negative emotional state...