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The effect of pitch tracking on automatic dialect identification

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Abstract

Pitch tracking is one of the most important research topics in the recognition and identification area. This study concerns the effect of the pitch tracking technique used on the accuracy and speed of automatic dialect identification. This effort was carried out using the TIMIT database. The pitch tracking procedures investigated are the Boersma algorithm, the iterative adaptive inverse filtering approach, and the summation of residual harmonics method. All else being equal, the summation of residual harmonics provided the highest accuracy as well as the fastest performance of the three methods.

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Acknowledgements

The authors would like to thank the reviewers for the detailed and valuable feedback which helped improve this manuscript.

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  1. Virginia Tech, Blacksburg, VA, 24061, USA

    A. Etman & A. A. Beex

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  1. A. Etman
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  2. A. A. Beex
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Correspondence to A. Etman.

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Etman, A., Beex, A.A. The effect of pitch tracking on automatic dialect identification. Int J Speech Technol 20, 629–634 (2017). https://doi.org/10.1007/s10772-017-9434-0

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  • DOI: https://doi.org/10.1007/s10772-017-9434-0

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