| 摘要 |
A method for reducing speech recognition errors. The method includes receiving an N-best list associated with a user utterance. The N-best list includes one or more hypotheses and associated confidence values. The user utterance is classified in response to the N-best list, resulting in a classification. A re-scoring algorithm that is tuned for the classification is selected. The re-scoring algorithm is applied to the N-best list to create a re-scored N-best list. A hypothesis for the value of the user utterance is selected based on the re-scored N-best list.
|
