| , informing , story-telling , etc . This | paper | addresses the problem of the automatic | #108 This paper addresses the problem of the automatic detection of those activities in meeting situation and everyday rejoinders. | ||
| infrastructure </term> for this purpose . In this | paper | we show how two standard outputs from <term> | #276 In this paper we show how two standard outputs from information extraction (IE) systems - named entity annotations and scenario templates - can be used to enhance access to text collections via a standard text browser. | ||
| machine learning techniques </term> . In this | paper | , we address the problem of combining several | #1029 In this paper, we address the problem of combining several language models (LMs). | ||
| conducted with the U.S. military . This | paper | proposes a practical approach employing | #1242 This paper proposes a practical approach employing n-gram models and error-correction rules for Thai key prediction and Thai-English language identification. | ||
| Thai-English language identification </term> . The | paper | also proposes <term> rule-reduction algorithm | #1263 The paper also proposes rule-reduction algorithm applying mutual information to reduce the error-correction rules. | ||
| one or more <term> sentences </term> . In this | paper | , we present <term> SPoT </term> , a <term> sentence | #1337 In this paper, we present SPoT, a sentence planner, and a new methodology for automatically training SPoT on the basis of feedback provided by human judges. | ||
| human-ranked sentence plan </term> . In this | paper | , we compare the relative effects of <term> | #1463 In this paper, we compare the relative effects of segment order, segmentation and segment contiguity on the retrieval performance of a translation memory system. | ||
| parsed in O ( n6 ) <term> time </term> . In this | paper | , we study a <term> parsing technique </term> | #1681 In this paper, we study a parsing technique whose purpose is to improve the practical efficiency of RCL parsers. | ||
| <term> syntactic paraphrases </term> . This | paper | presents a formal analysis for a large | #1817 This paper presents a formal analysis for a large class of words called alternative markers, which includes other (than), such (as), and besides. | ||
| or rule-based approaches </term> . In this | paper | We experimentally evaluate a <term> trainable | #2053 In this paper We experimentally evaluate a trainable sentence planner for a spoken dialogue system by eliciting subjective human judgments. | ||
| relationships among the target variables . This | paper | describes a method for <term> utterance classification | #2207 This paper describes a method for utterance classification that does not require manual transcription of training data. | ||
| average precision metric </term> . In this | paper | we present <term> ONTOSCORE </term> , a system | #2438 In this paper we present ONTOSCORE, a system for scoring sets of concepts on the basis of an ontology. | ||
| the performance of our systems . In this | paper | , we introduce a <term> generative probabilistic | #2670 In this paper, we introduce a generative probabilistic optical character recognition (OCR) model that describes an end-to-end process in the noisy channel framework, progressing from generation of true text through its transformation into the noisy output of an OCR system. | ||
| conversational speech </term> are limited . In this | paper | , we show how <term> training data </term> | #3031 In this paper, we show how training data can be supplemented with text from the web filtered to match the style and/or topic of the target recognition task, but also that it is possible to get bigger performance gains from the data by using class-dependent interpolation of N-grams. | ||
| </term> for some <term> NE types </term> . In this | paper | , we describe a <term> phrase-based unigram | #3392 In this paper, we describe a phrase-based unigram model for statistical machine translation that uses a much simpler set of model parameters than similar phrase-based models. | ||
| </term> and <term> phrase length </term> . In this | paper | , we propose a novel <term> Cooperative Model | #3480 In this paper, we propose a novel Cooperative Model for natural language understanding in a dialogue system. | ||
| question answering session </term> . In this | paper | we present a novel , customizable <term> | #3714 In this paper we present a novel, customizable IE paradigm that takes advantage of predicate-argument structures. | ||
| high quality <term> IE results </term> . This | paper | proposes the <term> Hierarchical Directed | #3791 This paper proposes the Hierarchical Directed Acyclic Graph (HDAG) Kernel for structured natural language data. | ||
| <term> new event detection </term> . In this | paper | we formulate <term> story link detection </term> | #4066 In this paper we formulate story link detection and new event detection as information retrieval task and hypothesize on the impact of precision and recall on both systems. | ||
| Experimental results validate our hypothesis . This | paper | concerns the <term> discourse understanding | #4128 This paper concerns the discourse understanding process in spoken dialogue systems. |
