Language Identification Using Excitation Source Features
This book discusses the contribution of excitation source information in discriminating language. The authors focus on the excitation source component of speech for enhancement of language identification (LID) performance. Language specific features are extracted using two different modes: (i) Implicit processing of linear prediction (LP) residual and (ii) Explicit parameterization of linear prediction residual. The book discusses how in implicit processing approach, excitation source features are derived from LP residual, Hilbert envelope (magnitude) of LP residual and Phase of LP residual; and in explicit parameterization approach, LP residual signal is processed in spectral domain to extract the relevant language specific features. The authors further extract source features from these modes, which are combined for enhancing the performance of LID systems. The proposed excitation source features are also investigated for LID in background noisy environments. Each chapter of this book provides the motivation for exploring the specific feature for LID task, and subsequently discuss the methods to extract those features and finally suggest appropriate models to capture the language specific knowledge from the proposed features. Finally, the book discuss about various combinations of spectral and source features, and the desired models to enhance the performance of LID systems.
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2 Language IdentificationA Brief Review
3 Implicit Excitation Source Features for Language Identification
4 Parametric Excitation Source Features for Language Identification
5 Complementary and Robust Nature of Excitation Source Features for Language Identification
6 Summary and Conclusion
Appendix AGaussian Mixture Model
Appendix BMelFrequency Cepstral Coefficient MFCCFeatures
Appendix CEvaluation of Excitation Source Featuresin Different Noisy Conditions
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cepstral cepstral coefficients combining the evidences components of LP computed Conference on Acoustics Dogri evaluation evidences obtained excitation source features excitation source information explicit LID explored feature vectors features of excitation filter frequency Gaussian mixture glottal cycle glottal flow implicit Indian languages K.S. Rao language discrimination task language identification language identification system language models language-specific excitation source language-specific information level features LID study LID systems developed LID task LP residual samples LP residual signal magnitude and phase MFCC feature Nagamese noise OGI-MLTS database parametric features phase components phase-III phoneme phonotactic prosodic prosodic features raw LP residual represents residual frame RMFCC robustness of excitation RP feature seg and supra seg level segmental and supra-segmental segmental level Signal Processing ICASSP Sindhi sound units speaker recognition spectral features speech corpus speech signal sub-segmental level supra levels supra-segmental levels systems are developed test utterances training data vocal folds vocal tract features