University of Twente Student Theses
Investigating the use of acoustic features to understand human social interaction from speech
Dieperink, D. (2023) Investigating the use of acoustic features to understand human social interaction from speech.
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| Abstract: | Computer analysis of human speech can enrich our human-computer interactions. Aside from automatic speech recognition, which is about translating speech into text, there are other speech analysis tasks, that include predicting social or emotional characteristics about a speaker based on certain properties of the sound they produce. This research will investigate the application of various machine learning methods to predict different kinds of characteristics from acoustic features that are computed from speech audio signals. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science |
| Programme: | Computer Science BSc (56964) |
| Link to this item: | https://purl.utwente.nl/essays/94371 |
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