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We improve the automatic speech recognition of broadcast news using paradigms from Web 2.0 to obtain time-and topic-relevant text data for language modeling. We elaborate an un-supervised text collection and decoding strategy that includes crawling appropriate texts from RSS Feeds, complementing it with texts from Twitter, language model and vocabulary(More)
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