| that is surprisingly close to what can be | achieved | using conventional <term> word-trigram recognition | #2246 The method combines domain independent acoustic models with off-the-shelf classifiers to give utterance classification performance that is surprisingly close to what can be achieved using conventional word-trigram recognition requiring manual transcription. | |
| impacts the <term> accuracy </term> that can be | achieved | by the <term> algorithms </term> , we present | #5572 Observing that the quality of the lexicon greatly impacts the accuracy that can be achieved by the algorithms, we present a method of HMM training that improves accuracy when training of lexical probabilities is unstable. | |
| <term> model </term> . The new <term> model </term> | achieved | 89.75 % <term> F-measure </term> , a 13 % relative | #8838 The new modelachieved 89.75% F-measure, a 13% relative decrease in F-measure error over the baseline model’s score of 88.2%. | |
| </term> for <term> SI recognition </term> , we | achieved | a 7.5 % <term> word error rate </term> on a | #17080 With only 12 training speakers for SI recognition, we achieved a 7.5% word error rate on a standard grammar and test set from the DARPA Resource Management corpus. | |
| <term> reduction in the search space </term> is | achieved | by using <term> semantic </term> rather than | #17711 A further reduction in the search space is achieved by using semantic rather than syntactic categories on the terminal and non-terminal edges, thereby reducing the amount of ambiguity and thus the number of edges, since only edges with a valid semantic interpretation are ever introduced. | |
| <term> robust parsing capability </term> was | achieved | through minor extensions of pre-existing | #19369 This robust parsing capability was achieved through minor extensions of pre-existing components already in place for the full linguistic analysis component. | |
| </term> of <term> grammatical knowledge </term> is | achieved | building upon the <term> head-oriented notions | #20833 Complete lexical distribution of grammatical knowledge is achieved building upon the head-oriented notions of valency and dependency, while inheritance mechanisms are used to capture lexical generalizations. |
