| other,4-3-H01-1058,ak | </term> . The <term> oracle </term> knows the <term> | reference word string | </term> and selects the <term> word string </term> | #1074 The oracle knows thereference word string and selects the word string with the best performance (typically, word or semantic error rate) from a list of word strings, where each word string has been obtained by using a different LM. | |
| tech,10-6-H01-1058,ak | method that mimics the behavior of the <term> | oracle | </term> using a <term> neural network </term> | #1162 We suggest a method that mimics the behavior of theoracle using a neural network or a decision tree. | |
| measure(ment),21-2-H01-1058,ak | performance </term> but fall short of the <term> | performance | </term> of an <term> oracle </term> . The <term> | #1065 We find that simple interpolation methods, like log-linear and linear interpolation, improve the performance but fall short of theperformance of an oracle. | |
| other,10-3-H01-1058,ak | word string </term> and selects the <term> | word string | </term> with the best <term> performance </term> | #1080 The oracle knows the reference word string and selects theword string with the best performance (typically, word or semantic error rate) from a list of word strings, where each word string has been obtained by using a different LM. | |
| model,17-7-H01-1058,ak | hypothesis </term> corresponding to the <term> | LM | </term> with the best <term> confidence </term> | #1189 The method amounts to tagging LMs with confidence measures and picking the best hypothesis corresponding to theLM with the best confidence. | |
| model,14-4-H01-1058,ak | </term> with hard decisions using the <term> | reference | </term> . We provide experimental results | #1129 Actually, the oracle acts like a dynamic combiner with hard decisions using thereference. | |
| measure(ment),7-7-H01-1058,ak | amounts to tagging <term> LMs </term> with <term> | confidence measures | </term> and picking the best <term> hypothesis | #1179 The method amounts to tagging LMs withconfidence measures and picking the best hypothesis corresponding to the LM with the best confidence. |
