Audiovisual articulatory inversion based on Gaussian Mixture Model (GMM) Akustik ve görsel veriler kullanilarak artikülatörlerin hareketlerinin Gauss Karişim Modellere (GKM) dayali kestirimi

Date

2010-12-01

Author

ÖZBEK, İbrahim Yücel
Demirekler, Mübeccel

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In this study, we examined articulatory inversion using audiovisual information based on Gaussian Mixture Model (GMM). In this method the joint distribution of the articulatory movement and audio (and/or visual) data are modelled via a mixture of Gaussians. The conditional expected value of the GMM is used as regression function between the audio (and/orvisual) and articulatory spaces. We also examined various fusion methods in order to combine acoustic and visual information in articulatory inversion. The fusion methods improve the performance of articulatory inversion. ©2010 IEEE.

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78651449722&origin=inward
https://hdl.handle.net/11511/106912

DOI

https://doi.org/10.1109/siu.2010.5653987

Conference Name

18th IEEE Signal Processing and Communications Applications Conference, SIU 2010

Collections

Graduate School of Natural and Applied Sciences, Conference / Seminar

Citation Formats

İ. Y. ÖZBEK and M. Demirekler, “Audiovisual articulatory inversion based on Gaussian Mixture Model (GMM) Akustik ve görsel veriler kullanilarak artikülatörlerin hareketlerinin Gauss Karişim Modellere (GKM) dayali kestirimi,” presented at the 18th IEEE Signal Processing and Communications Applications Conference, SIU 2010, Diyarbakır, Türkiye, 2010, Accessed: 00, 2023. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78651449722&origin=inward.