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Emotional speech synthesis by XML file using interactive genetic algorithms
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ACM/SIGEVO Summit on Genetic and Evolutionary Computation archive
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation table of contents
Shanghai, China
POSTER SESSION: Poster sessions table of contents
Pages 907-910  
Year of Publication: 2009
ISBN:978-1-60558-326-6
Authors
Siliang Lv  Department of Computer Science and Technology, Key Laboratory of Software in Computing and Communication in Anhui, USTC, Hefei, China
Shangfei Wang  Department of Computer Science and Technology, Key Laboratory of Software in Computing and Communication in Anhui, USTC, Hefei, China
Xufa Wang  Department of Computer Science and Technology, Key Laboratory of Software in Computing and Communication in Anhui, USTC, Hefei, China
Sponsors
SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

As a technique that can "let computer speak", speech synthesis is drawing more and more attention. Today, much speech synthesis software can synthesize neutral speech naturally and knowingly. However, it is hard to make computers speak with "emotion" as that in our daily life, because of the complexity of emotion model. Interactive Genetic Algorithms which can be acted self-organizingly, adaptively and self-learningly can just resolve the problem of difficulty in modeling emotional speech synthesis. As a result, this paper designs an emotional speech synthesis process, which adjusts the parameters (XML-tags) used to synthesize emotional speech dynamically, using interactive Genetic Algorithms, to optimize the quality of emotional speech. Also, the paper includes an evaluation experiment, which proves the feasibility of the algorithms.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
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2
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Collaborative Colleagues:
Siliang Lv: colleagues
Shangfei Wang: colleagues
Xufa Wang: colleagues