J01-3002 have presented a formal model of word discovery in continuous speech . The main
E09-3001 full fidelity when required . Key Word Discovery The milestone set for all systems
W03-1724 to the lack of a module for OOV word discovery . It only gets a small number
W14-6816 adding lexical feature and new words discovery . In Section 2 , we describe
J01-3002 statistical model for segmentation and word discovery in continuous speech is presented
I05-3021 identification and nice potential in OOV word discovery . However , its weakness in handling
E09-3001 paper ; automatic segmentation and word discovery . The automatic segmentation
E06-2023 probabilistic model structure for word discovery . He uses a minimum representation
J01-4015 Brian Roark Statistical Model for Word Discovery in John Bateman Thomas Kamps
W04-1713 Significant techniques include unknown word discovery , clustering and other issues
W11-0305 could use for segmentation and word discovery during language ac - quisition
J01-3002 <title> A Statistical Model for Word Discovery in Transcribed Speech </title>
W03-1724 e.g. , out-of-vocabulary ( OOV ) word discovery . 1 Introduction After about
W09-3425 training Processing includes a new word discovery function and Normal Segmentation
P15-2074 segmentation system SegT with unknown word discovery to show the positive effect of
J01-3002 possesses significant other cues for word discovery . However , it is still a matter
W10-4131 achieve a certain level of OOV word discovery in closed training evaluation
D09-1157 cascaded simpler tasks of cue word discovery and binary relation classification
P03-1036 algorithms for text segmentation and word discovery , such as ( Deligne and Bimbot
I05-3021 items is inadequate for the OOV word discovery task . Nevertheless , its RIV
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