W04-2904 provide better discrimination for wordspotting . These can also be used to diagnose
W04-2904 generating and evaluating scores from wordspotting systems have been proposed .
H05-1119 FOM ) metric defined by NIST for wordspotting evaluations . In its original
W04-2904 Mark Abstract When evaluating wordspotting systems , one normally compares
H93-1022 large-vocabulary recognizer for the wordspotting task , can lead to dramatic improvements
H94-1042 Spotting , which is an extension of wordspotting where the goal is to determine
W04-2904 were conducted using the Nexidia wordspotting system trained on broadcast quality
H93-1076 In contrast with most previous wordspotting applications ( e.g. , \ -LSB-
H93-1076 algorithms for an interactive wordspotting system " . Proceedings of ICASSP-92
H93-1076 , L. and Bush , M. " HMM-based wordspotting for voice editing and audio indexing
H93-1023 to topic identification using wordspotting is described in \ -LSB- 1 \ -RSB-
H94-1073 by the cosine measure . Current wordspotting systems report high detection
H05-1119 is closely related to popular wordspotting metrics , such as the NIST (
H93-1022 significantly outperforms the traditional wordspotting approach for all false alarm
H94-1073 been investigated very little . A wordspotting system for voice indexing was
W04-2904 These scores are what the Nexidia wordspotting product reveals to the users
W04-2904 <title> Scoring Algorithms for Wordspotting Systems </title> Robert W Morris
P05-1055 NIST , www ) -- but rather uses wordspotting measures , which are more technologyrather
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