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A post-processing system to yield reduced word error rates: Recognizer Output Voting Error Reduction (ROVER)
  • J. Fiscus
  • Computer Science
  • IEEE Workshop on Automatic Speech Recognition and…
  • 14 December 1997
TLDR
A post-recognition process which models the output generated by multiple ASR systems as independent knowledge sources that can be combined and used to generate an output with reduced error rate. Expand
TRECVID 2015 - An Overview of the Goals, Tasks, Data, Evaluation Mechanisms and Metrics
The TREC Video Retrieval Evaluation (TRECVID) 2011 was a TREC-style video analysis and retrieval evaluation, the goal of which remains to promote progress in content-based exploitation of digitalExpand
REDUCED WORD ERROR RATES
This paper describes a system developed at NIST to produce a composite Automatic Speech Recognition (ASR) system output when the outputs of multiple ASR systems are available, and for which, in manyExpand
Results of the 2006 Spoken Term Detection Evaluation
TLDR
The paper describes the evaluation task posed to Spoken Term Detection systems, the evaluation methodologies, the Arabic, English and Mandarin evaluation corpora, and the results of the evaluation. Expand
The Rich Transcription 2006 Spring Meeting Recognition Evaluation
We present the design and results of the Spring 2006 (RT-06S) Rich Transcription Meeting Recognition Evaluation; the fourth in a series of community-wide evaluations of language technologies in theExpand
Topic detection and tracking evaluation overview
TLDR
This chapter introduces TDT's evaluation methodology including: the Linguistic Data Consortium's TDT corpora, evaluation metrics used in TDT and the five TDT research tasks: Topic Tracking, Link Detection, Topic Detection, First Story Detection, and Story Segmentation. Expand
TRECVID 2016: Evaluating Video Search, Video Event Detection, Localization, and Hyperlinking
TLDR
TRECVID 2016: Evaluating Video Search, Video Event Detection, Localization, and Hyperlinking George Awad, Jonathan Fiscus, David Joy, Martial Michel, Alan Smeaton, Wessel Kraaij, Maria Eskevich, Robin Aly, Roeland Ordelman, Marc Ritter, et al. Expand
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