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- W1831493390 abstract "In our work to design a spoken language translator between South African languages we found the project inflexible and much bigger than first anticipated. The first part of the project was to design a system that will perform language identification. This paper investigates a language identification (LID) task using three South African languages. The problem is investigated solely from the signal processing perspective using linear predictive coding (LPC)-based and parameterized discrete Fourier transform (DFT)-based feature-sets. Six minute speech data was collected from a talker in all three languages. The LID system uses five second samples of speech in the three languages to perform identification. The results show that a DFT-based parameterized feature-set significantly lowered the error rate. The lowest error rate is obtained at a spectral compression lower than the mel-scale." @default.
- W1831493390 created "2016-06-24" @default.
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- W1831493390 date "2002-11-27" @default.
- W1831493390 modified "2023-09-25" @default.
- W1831493390 title "Language identification system for South African languages" @default.
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- W1831493390 doi "https://doi.org/10.1109/comsig.1998.736947" @default.
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