Papers with rescoring framework
Session-level Language Modeling for Conversational Speech (D18-1)
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| Challenge: | Xiong et al., 2017) generalizes language models for conversational speech recognition . recurrent neural networks (RNNs) read a list of words sequentially and predict the next word at each position. |
| Approach: | They propose to generalize language models for conversational speech recognition to capture conversation-level phenomena such as adjacency pairs, lexical entrainment, and topical coherence. |
| Outcome: | The proposed model reduces perplexity and improves word error rate over standard models in the conversational telephone speech domain. |