| this basic idea are being discussed and/or | evaluated | : Similar to activities one can define <term> | #136 Several extensions of this basic idea are being discussed and/or evaluated: Similar to activities one can define subsets of larger database and detect those automatically which is shown on a large database of TV shows. | ||
| </term> . In this paper We experimentally | evaluate | a <term> trainable sentence planner </term> | #2056 In this paper We experimentally evaluate a trainable sentence planner for a spoken dialogue system by eliciting subjective human judgments. | ||
| perform an exhaustive comparison , we also | evaluate | a <term> hand-crafted template-based generation | #2082 In order to perform an exhaustive comparison, we also evaluate a hand-crafted template-based generation component, two rule-based sentence planners, and two baseline sentence planners. | ||
| classification accuracy </term> of the method is | evaluated | on three different <term> spoken language | #2298 The classification accuracy of the method is evaluated on three different spoken language system domains. | ||
| and/or answer levels </term> . Experiments | evaluating | the effectiveness of our <term> answer resolution | #2398 Experiments evaluating the effectiveness of our answer resolution algorithm show a 35.0% relative improvement over our baseline system in the number of questions correctly answered, and a 32.8% improvement according to the average precision metric. | ||
| decoding algorithm </term> that enables us to | evaluate | and compare several , previously proposed | #2554 We propose a new phrase-based translation model and decoding algorithm that enables us to evaluate and compare several, previously proposed phrase-based translation models. | ||
| evaluation methods </term> for automatically | evaluating | the <term> summarization quality </term> of | #2852 Furthermore, we propose the use of standard parser evaluation methods for automatically evaluating the summarization quality of sentence condensation systems. | ||
| intervals in the <term> French sentence </term> . We | evaluate | the utility of this <term> constraint </term> | #3261 We evaluate the utility of this constraint in two different algorithms. | ||
| and <term> sentence alignment tasks </term> to | evaluate | its performance as a <term> similarity measure | #3853 We applied the proposed method to question classification and sentence alignment tasks to evaluate its performance as a similarity measure and a kernel function. | ||
| most promising <term> features </term> . We | evaluate | the system on twenty <term> Switchboard dialogues | #4020 We evaluate the system on twenty Switchboard dialogues and show that it compares well to Byron's (2002) manually tuned system. | ||
| supervised learning </term> . In this paper , we | evaluate | an approach to automatically acquire <term> | #4828 In this paper, we evaluate an approach to automatically acquire sense-tagged training data from English-Chinese parallel corpora, which are then used for disambiguating the nouns in the SENSEVAL-2 English lexical sample task. | ||
| issue of <term> domain dependence </term> in | evaluating | <term> WSD programs </term> . We describe the | #4930 Our analysis also highlights the importance of the issue of domain dependence in evaluating WSD programs. | ||
| paradigm </term> . We report experiences and | evaluate | the <term> annotated data </term> from the | #4983 We report experiences and evaluate the annotated data from the first project stage. | ||
| called <term> POURPRE </term> , for automatically | evaluating | answers to <term> definition questions </term> | #5935 Following recent developments in the automatic evaluation of machine translation and document summarization, we present a similar approach, implemented in a measure called POURPRE, for automatically evaluating answers to definition questions. | ||
| increasingly common speculative claim , by | evaluating | a representative <term> Chinese-to-English | #6344 We present the first known empirical test of an increasingly common speculative claim, by evaluating a representative Chinese-to-English SMT model directly on word sense disambiguation performance, using standard WSD evaluation methodology and datasets from the Senseval-3 Chinese lexical sample task. | ||
| Much effort has been put in designing and | evaluating | dedicated <term> word sense disambiguation | #6380 Much effort has been put in designing and evaluating dedicated word sense disambiguation (WSD) models, in particular with the Senseval series of workshops. | ||
| </term> of <term> SMT models </term> has never been | evaluated | and compared with that of the dedicated | #6449 Surprisingly however, the WSD accuracy of SMT models has never been evaluated and compared with that of the dedicated WSD models. | ||
| producing promising results , which we have | evaluated | according to <term> cost-efficiency </term> | #7551 Our preliminary experiments on building a paraphrase corpus have so far been producing promising results, which we have evaluated according to cost-efficiency, exhaustiveness, and reliability. | ||
| be inferred . A <term> paraphrase </term> is | evaluated | for whether its <term> sentences </term> are | #7736 A paraphrase is evaluated for whether its sentences are used in the same context. | ||
| non-parallel newspaper corpora </term> . We | evaluate | the qualityof the extracted data by showing | #8409 We evaluate the qualityof the extracted data by showing that it improves the performance of a state-of-the-art statisticalmachine translation system. |
