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28 December 2022 Is it possible to predict speaker’s body size and oral cavity characteristics from speech signals: a preliminary study on Mandarin Chinese
Puyang Geng, Hong Guo, Qimeng Lu, Jinhua Zeng, Yan Li
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Proceedings Volume 12506, Third International Conference on Computer Science and Communication Technology (ICCSCT 2022); 125062P (2022) https://doi.org/10.1117/12.2661788
Event: International Conference on Computer Science and Communication Technology (ICCSCT 2022), 2022, Beijing, China
Abstract
This paper proposes a study on whether the speaker’s body size (height, weight) and oral cavity (lip protrusion LP, lip opening LO, front cavity FC) characteristics can be predicted based on the acoustic features of speech. Firstly, Pearson’s correlation analysis was first conducted to examine the relationships between acoustic features and body size and oral cavity characteristics. Further, the effects of acoustic features in predicting body size and oral cavity characteristics were examined using random forest and decision tree models. The results showed that fundamental frequency statistics (i.e., mean, max, min) exhibited significant negative correlations with height, weight, and FC. Besides, good accuracies of classification in height, LP range, LO range, and FC range could be achieved based on the acoustic features. The findings in the current paper imply that acoustic features could be the potential features for identification of the speaker’s body size and oral cavity characteristics. This paper will not only contribute to the research and practices in forensic speaker profiling and but also provides foundations for the technology of automatic speaker recognition.
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Puyang Geng, Hong Guo, Qimeng Lu, Jinhua Zeng, and Yan Li "Is it possible to predict speaker’s body size and oral cavity characteristics from speech signals: a preliminary study on Mandarin Chinese", Proc. SPIE 12506, Third International Conference on Computer Science and Communication Technology (ICCSCT 2022), 125062P (28 December 2022); https://doi.org/10.1117/12.2661788
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KEYWORDS
Acoustics
Laser induced plasma spectroscopy
Sensors
Forensic science
Profiling
Head
Speaker recognition
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