Improved Acoustic Modeling for Continuous Speech Recognition

Expanding the Domain of a Multi lingual Speech to Speech Translation System E x p a n d i n g t h e D o m a i n o f a M u l t i l i n g u a l S p e e c h t o S p e e c h T r a n s l a t i

Learning Intonation Rules for Concept to Speech Generation L e a r n i n g I n t o n a t i o n R u l e s for C o n c e p t t o S p e e c h G e n e r a t i o n S h i m e i P a n a n d K a

Word Boundary Identification from Phoneme Sequence Constraints in Automatic Continuous Speech Recognition W o r d B o u n d a r y I d e n t i f i c a t i o n fro m P h o n e m e S e q u e

vIicrophone Arrays and Neural Networks for Robust Speech Recognition vIicrophone Arrays and N e u r a l N e t w o r k s for R o b u s t S p e e c h R e c o g n i t i o n C Che +, Q Lin +,

BYBLOS SPEECH RECOGNITION BENCHMARK RESULTS B Y B L O S S P E E C H R E C O G N I T I O N B E N C H M A R K R E S U L T S F Kubala, S Austin, C Barry, J Makhoul, P Placeway, R Schwartz

THE MINDS SYSTEM USING CONTEXT AND DIALOG TO ENHANCE SPEECH RECOGNITION T H E M I N D S S Y S T E M U S I N G C O N T E X T A N D D I A L O G T O E N H A N C E S P E E C H R E C O G N I T

A STACK DECODER FOR CONTINOUS SPEECH RECOGNITION A S T A C K D E C O D E R F O R C O N T I N O U S S P E E C H R E C O G N I T I O N 1 D e a n G S t u r t e v a n t D r a g o n Systems,

Contextually Based Data Derived Pronunciation Networks for Automatic Speech Recognition C o n t e x t u a l l y B a s e d D a t a D e r i v e d P r o n u n c i a t i o n N e t w o r k s