We describe the latest version of Microsoft’s conversational speech recognition system for the Switchboard and CallHome domains.\u00a0 The system adds a CNN-BLSTM acoustic model to the set of model architectures we combined previously, and includes character-based and dialog session aware LSTM language models in rescoring.\u00a0 For system combination we adopt a two-stage approach, whereby acoustic model posteriors are first combined at the senone\/frame level,followed by a word-level voting via confusion networks.\u00a0 We also added another language model rescoring step following the confusion network combination.\u00a0 The resulting system yields a 5.1% word error rate on the NIST 2000 Switchboard test set, and 9.8% on the CallHome subset.<\/p>\n","protected":false},"excerpt":{"rendered":"
We describe the latest version of Microsoft’s conversational speech recognition system for the Switchboard and CallHome domains.\u00a0 The system adds a CNN-BLSTM acoustic model to the set of model architectures we combined previously, and includes character-based and dialog session aware LSTM language models in rescoring.\u00a0 For system combination we adopt a two-stage approach, whereby acoustic 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