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Books > Computing & IT > Applications of computing > Artificial intelligence > Natural language & machine translation
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Speech Recognition Using Articulatory and Excitation Source Features (Paperback, 1st ed. 2017)
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Speech Recognition Using Articulatory and Excitation Source Features (Paperback, 1st ed. 2017)
Series: SpringerBriefs in Speech Technology
Expected to ship within 10 - 15 working days
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This book discusses the contribution of articulatory and excitation
source information in discriminating sound units. The authors focus
on excitation source component of speech -- and the dynamics of
various articulators during speech production -- for enhancement of
speech recognition (SR) performance. Speech recognition is analyzed
for read, extempore, and conversation modes of speech. Five groups
of articulatory features (AFs) are explored for speech recognition,
in addition to conventional spectral features. Each chapter
provides the motivation for exploring the specific feature for SR
task, discusses the methods to extract those features, and finally
suggests appropriate models to capture the sound unit specific
knowledge from the proposed features. The authors close by
discussing various combinations of spectral, articulatory and
source features, and the desired models to enhance the performance
of SR systems.
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