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- W1564887926 abstract "This paper describes the latest Speech-to-Text system developed for the Global Autonomous Language Exploitation (“GALE”) domain by Carnegie Mellon University (CMU). This systems uses discriminative training, bottle-neck features and other techniques that were not used in previous versions of our system, and is trained on 1150 hours of data from a variety of Arabic speech sources. In this paper, we show how different lexica, pre-processing, and system combination techniques can be used to improve the final output, and provide analysis of the improvements achieved by the individual techniques. Index Terms: speech recognition, discriminative training, bottle-neck features" @default.
- W1564887926 created "2016-06-24" @default.
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- W1564887926 date "2010-09-26" @default.
- W1564887926 modified "2023-10-16" @default.
- W1564887926 title "The 2010 CMU GALE speech-to-text system" @default.
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- W1564887926 doi "https://doi.org/10.21437/interspeech.2010-439" @default.
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