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Language Identification Using Excitation Source Features (Paperback, 2015 ed.)
Loot Price: R1,796
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Language Identification Using Excitation Source Features (Paperback, 2015 ed.)
Series: SpringerBriefs in Speech Technology
Expected to ship within 10 - 15 working days
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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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