The effect of pitch tracking on automatic dialect identification

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 t...

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Bibliographic Details
Published inInternational journal of speech technology Vol. 20; no. 3; pp. 629 - 634
Main Authors Etman, A., Beex, A. A.
Format Journal Article
LanguageEnglish
Published New York Springer US 01.09.2017
Springer Nature B.V
Subjects
Adaptive algorithms
Adaptive filters
Algorithms
Artificial Intelligence
Engineering
Harmonics
Identification
Regional dialects
Signal,Image and Speech Processing
Social Sciences
Tracking
Automatic dialect identification (ADI)
Pitch tracking algorithms
Boersma
IAIF
SRH
Prosodic features
Phonotactic features
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Summary: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.
ISSN:1381-2416
1572-8110
DOI:10.1007/s10772-017-9434-0