Jointly Encoding Word Confusion Network and Dialogue Context with BERT for Spoken Language Understanding

Understand

Spoken Language Understanding (SLU) converts hypotheses from automatic speech recognizer (ASR) into structured semantic representations.

• ASR recognition errors can severely degenerate the performance of the subsequent SLU module.
• To address this issue, word confusion networks (WCNs) have been used to encode the input for SLU, which contain richer information than 1-best or n-best hypotheses list.
• To further eliminate ambiguity, the last system act of dialogue context is also utilized as additional input.