| needs a <term> computational lexicon </term> , | each | <term> system </term> puts different amounts | #15925 Although every natural language system needs a computational lexicon, each system puts different amounts and types of information into its lexicon according to its individual needs. | |
| mapping </term> is estimated independently for | each | <term> training ( reference ) speaker </term> | #17159 A probabilistic spectral mapping is estimated independently for each training (reference) speaker and the target speaker. | |
| </term> and the <term> target speaker </term> . | Each | <term> reference model </term> is transformed | #17170 A probabilistic spectral mapping is estimated independently for each training (reference) speaker and the target speaker. Each reference model is transformed to the space of the target speaker and combined by averaging. | |
| </term> , performance degrades gracefully . | Each | of these techniques have been evaluated | #17527 For pragmatics processing, we describe how the method of abductive inference is inherently robust, in that an interpretation is always possible, so that in the absence of the required world knowledge, performance degrades gracefully. Each of these techniques have been evaluated and the results of the evaluations are presented. | |
| </term> of its <term> search space </term> . As | each | new <term> edge </term> is added to the <term> | #17601 As each new edge is added to the chart, the algorithm checks only the topmost of the edges adjacent to it, rather than all such edges as in conventional treatments. |
