Boers, J. (2006) On the Synthesis of Aggressive Vowels: Towards more robust aggression detection. Master's Thesis / Essay, Artificial Intelligence.
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Abstract
Sound and speech recognition are important research areas in artificial intelligence. Humans are very well able to detect aggression in verbal expressions. Knowledge of the relation between emotions, e.g. aggression, and acoustic features in speech may be of much use improving, for instance, speech recognition. Currently, Sound hitelligence is working on the development of the next generation of aggression detectors. Those systems are aimed at not only detecting aggression, but also classifying verbal expressions of human aggression(in real-life circumstances). Much research is done on the perceptual side of the speech chain. However, in order to come to aggression classification we focus on the speech production of Dutch vowels. Parallel to human speech production, we developed, implemented, and evaluated a vocoder which was used to synthesize vowels intended to exhibit gradations of emotions, primarily aggression. In contrast to former research on human recognition of verbal emotions, normally conducted on genuine, rich and labeled data we defined cues and subsequently synthesized vowels. By means of a psycho-acoustic experiment we believe to have proven that this approach, and thus the vocoder, is scientific justified. Still, aggression classification needs much more further research —and it is our belief that nonlinear analysis might be very useful here (literature shows very interesting progress)— but either way, a vocoder, like the one used in this work, is expected to be complementary to current research approaches.
| Item Type: | Thesis (Master's Thesis / Essay) |
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| Degree programme: | Artificial Intelligence |
| Thesis type: | Master's Thesis / Essay |
| Language: | English |
| Date Deposited: | 15 Feb 2018 07:30 |
| Last Modified: | 15 Feb 2018 07:30 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/9069 |
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