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Spectral Feature Based Kannada Dialect Classification from Stop Consonants

  • Nagaratna B. ChittaragiEmail author
  • Pradyoth Hegde
  • Siva Krishna P. Mothukuri
  • Shashidhar G. Koolagudi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11941)

Abstract

This study focuses on the investigation of the significance of stop consonants in view of the classification of Kannada dialects. Majority of the studies proposed have shown the existence of evidential differences in the pronunciation of vowels across dialects. However, consonant based studies on dialect processing are found to be comparatively lesser. In this work, eight stop consonants are used for characterization of five Kannada dialects. Acoustic characteristics such as cepstral coefficients, formant frequencies, spectral flux, and rolloff features are explored from spectral analysis of stops. The consonant dataset is derived from standard Kannada dialect dataset consisting of 2417 consonants obtained from 16 native speakers from each dialect. Support vector machine (SVM) and decision tree-based extreme gradient boosting (XGB) ensemble classification methods are employed for automatic recognition of Kannada dialects. The research findings show that the stops existing for shorter duration also convey dialectal linguistic cues. Combination of spectral properties has contributed to the identification of distinct dialect-specific information across Kannada dialects.

Keywords

Kannada dialect classification Stop consonants Spectral features SVM XGB 

Notes

Acknowledgment

This work is supported by DST-GOI (Department of Science and Technology, Government of India) sponsored project entitled Characterization and Identification of Dialects in the Kannada Language.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Nagaratna B. Chittaragi
    • 1
    • 2
    Email author
  • Pradyoth Hegde
    • 1
  • Siva Krishna P. Mothukuri
    • 1
  • Shashidhar G. Koolagudi
    • 1
  1. 1.Department of Computer Science and EngineeringNational Institute of Technology KarnatakaSurathkalIndia
  2. 2.Department of Information Science and EngineeringSiddaganga Institute of TechnologyTumkurIndia

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