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) Impli...

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Bibliographic Details
Main Authors: Rao, K. Sreenivasa, Nandi, Dipanjan (Author)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2015, 2015
Edition:1st ed. 2015
Series:SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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100 1 |a Rao, K. Sreenivasa 
245 0 0 |a Language Identification Using Excitation Source Features  |h Elektronische Ressource  |c by K. Sreenivasa Rao, Dipanjan Nandi 
250 |a 1st ed. 2015 
260 |a Cham  |b Springer International Publishing  |c 2015, 2015 
300 |a XII, 119 p. 19 illus., 3 illus. in color  |b online resource 
505 0 |a Introduction -- Language Identification--A Brief Review -- Implicit Excitation Source Features for Language Identification -- Parametric Excitation Source Features for Language Identification -- Complementary and Robust Nature of Excitation Source Features for Language Identification -- Conclusion 
653 |a Signal, Image and Speech Processing 
653 |a Image processing 
653 |a Computational linguistics 
653 |a Computational Linguistics 
653 |a Speech processing systems 
653 |a Signal processing 
653 |a Natural Language Processing (NLP) 
653 |a Natural language processing (Computer science) 
700 1 |a Nandi, Dipanjan  |e [author] 
041 0 7 |a eng  |2 ISO 639-2 
989 |b Springer  |a Springer eBooks 2005- 
490 0 |a SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning 
856 4 0 |u https://doi.org/10.1007/978-3-319-17725-0?nosfx=y  |x Verlag  |3 Volltext 
082 0 |a 621.382 
520 |a 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