A ROBUST ENSEMBLE MODEL FOR SPOKEN LANGUAGE RECOGNITION

Nancy  WOODS; Gideon  BABATUNDE

doi:10.23743/acs-2020-21

A ROBUST ENSEMBLE MODEL FOR SPOKEN LANGUAGE RECOGNITION

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Published: Sep 30, 2020

DOI: https://doi.org/10.23743/acs-2020-21

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DOI

https://doi.org/10.23743/acs-2020-21

Authors

Nancy WOODS

chyn.woods@gmail.com

University of Ibadan, Faculty of Science, Department of Computer Science, Oyo State Ibadan

Gideon BABATUNDE

gideonbabs2@yahoo.com

* University of Ibadan, Faculty of Science, Department of Computer Science, Oyo State Ibadan

Abstract

Effective decision-making in industry conditions requires access and proper presentation of manufacturing data on the realised manufacturing process. Although the frequently applied ERP systems allow for recording economic events, their potential for decision support is limited. The article presents an original system for reporting manufacturing data based on Business Intelligence technology as a support for junior and middle management. As an example a possibility of utilising data from ERP systems to support decision-making in the field of purchases and logistics in small and medium enterprises.

Keywords:

Spoken Language Recognition, Computer Vision, Image Recognition, CNN

References

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Article Details

WOODS, N. ., & BABATUNDE, G. . (2020). A ROBUST ENSEMBLE MODEL FOR SPOKEN LANGUAGE RECOGNITION. Applied Computer Science, 16(3), 56–68. https://doi.org/10.23743/acs-2020-21

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