NDLI: A framework towards expressive speech analysis and synthesis with preliminary results

Content Provider	Springer Nature Link
Author	Raptis, Spyros Karabetsos, Sotiris Chalamandaris, Aimilios Tsiakoulis, Pirros
Copyright Year	2015
Abstract	Emotion-aware computing presents one of the key challenges in contemporary natural human interaction research in which emotional speech is an essential modality in multimodal user interfaces. Speech modality relates mainly to speech emotion and affect recognition as well as near natural expressive speech synthesis, the latter being considered as one of the next significant milestones in speech synthesis technology. A common problem to recognizing as well as to generating affective and emotional speech content is the adopted methodology on emotion analysis and modeling. This work proposes a generalized framework for annotating, analyzing and modeling expressive speech in a data-driven machine learning approach, towards building expressive text to speech synthesis systems. To this end, the framework as well as the data driven methodology is described, comprised of the techniques and approaches for acoustic analysis and expression clustering. In addition, the deployment of online experimental tools for speech perception and annotation and the description of the utilized speech data together with initial experimental results are also given, depicting the potential of the proposed framework and providing encouraging indications for further research.
Starting Page	387
Ending Page	394
Page Count	8
File Format	PDF
ISSN	17837677
Journal	Journal on Multimodal User Interfaces
Volume Number	9
Issue Number	4
e-ISSN	17838738
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2015-06-29
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Emotion classification Emotional speech Expressive speech Text to speech Acoustic analysis Speech synthesis User Interfaces and Human Computer Interaction Signal, Image and Speech Processing Image Processing and Computer Vision
Content Type	Text
Resource Type	Article
Subject	Signal Processing Human-Computer Interaction

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